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	23-35calculated 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 and the total forest (pairs of values in ), but they do in the private 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 and the total forest of the Plateau has decreased. For the private 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 and total forest.

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

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

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

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

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

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

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

Procedure

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

Answer

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

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

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

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

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

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

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

Procedure

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

Answer

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

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

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

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

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

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

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

Example 8: Standard error and combination of variable expressions

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

The standard error increases as the level of detail increases.

Large standard errors are to be expected if:

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

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

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

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5. Two types of changes?

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

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

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

The results are:

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

Example 9: : Additivity/non-additivity of changes

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

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

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

Example 10: Average number of years per domain

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

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

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

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

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

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

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

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

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

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

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NFI4—NFI5
change: total wood volume (stemwood)
main tree species · tree state (living/dead)
regional demarcation: forest district (2024)
unit: 1000 m³
evaluation area: accessible forest without shrub forest NFI1-NFI5
grid: 1.4 km grid, subgrids 1-5
change 2009/17–2018/26
		forest district (2024)
		AG01		AG02		AG03		AG04		AI01		AR01		BE01		BE02		BE03		BE04		BSBL01		BSBL02		BSBL03		BSBL04		FR01		FR02		FR03		FR04		GE01		GL01		GR01		GR02		GR03		GR04		GR05		JU01		LU01		LU02		LU03		NE01		NE02		NE03		NE04		NE06		NW01		OW01		OW02		SG01		SG02		SG03		SG04		SG05		SH01		SO01		SO02		SO03		SO04		SZ01		SZ02		SZ03		TG01		TG02		TG03		TI01		TI02		TI03		TI04		TI05		TI06		TI07		TI08		TI09		UR01		UR02		UR03		VD02		VD03		VD04		VD05		VD06		VD07		VD08		VD09		VD11		VD12		VD14		VD15		VD16		VD18		VD20		VD22		VS01		VS02		VS03		ZG01		ZH01		ZH02		ZH03		ZH04		ZH05		ZH06		ZH07		lakes		Switzerland
main tree species	tree state (living/dead)	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%
n/a	n/a	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.
	living	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.
	dead	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.
	total	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.
spruce	n/a	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.
	living	-32	341	-13	1392	65	155	-628	59	242	72	-780	51	-561	142	-1129	43	-1083	60	-658	46	43	84	-23	211	10	495	.	.	-40	183	-362	72	-177	217	507	41	4	75	-665	61	448	69	466	63	-46	1092	189	269	72	455	-534	65	-224	81	-138	128	-1147	59	-71	67	215	49	-152	72	18	364	-149	75	230	59	124	74	491	57	333	35	163	129	53	708	-127	151	-316	116	-500	50	-64	223	-272	83	-43	255	30	72	-473	63	192	94	-59	274	137	56	-205	73	-535	52	47	308	1145	76	-548	63	.	.	18	100	6	100	79	61	14	67	122	48	38	196	201	73	-127	256	127	60	274	37	24	730	-13	699	-51	135	31	273	42	178	-88	94	-137	91	36	130	-122	80	-395	58	-135	85	-126	103	-101	86	65	64	353	73	78	337	386	70	192	44	-367	87	45	376	122	123	20	949	-685	59	-270	80	-8	830	.	.	-6882	36
	dead	-27	88	-18	93	-19	233	18	280	14	149	131	69	-73	286	54	210	48	112	316	55	-16	100	9	186	0	37217	.	.	-36	89	-118	54	-254	90	15	261	.	.	-1	5906	-12	688	9	628	434	56	202	60	248	41	232	47	44	142	0	10158	42	287	5	88	22	99	11	104	43	97	117	104	9	147	-31	100	143	56	-20	78	20	219	20	380	-12	134	62	79	191	90	-7	128	-12	81	0	100	9	109	-23	218	128	67	53	72	7	82	-4	682	161	58	23	78	106	103	272	51	.	.	.	.	.	.	11	96	3	121	-2	100	23	97	35	69	4	1340	-6	126	30	181	127	74	43	96	.	.	10	84	-41	100	34	71	27	86	-4	140	52	62	16	171	-12	160	-33	117	16	100	-7	201	246	39	302	43	134	76	12	103	181	88	31	202	-6	601	-3	288	-6	459	7	100	-24	80	.	.	3736	19
	total	-59	183	-31	576	46	239	-610	56	256	73	-649	60	-634	131	-1075	46	-1035	63	-342	73	27	78	-14	366	10	436	.	.	-76	104	-480	61	-432	102	522	41	4	75	-666	62	436	78	475	63	388	98	390	119	320	99	-302	113	-180	88	-138	126	-1105	60	-66	73	237	45	-141	77	61	115	-32	399	239	56	93	103	634	53	313	36	183	114	73	503	-139	139	-254	136	-309	58	-71	200	-284	80	-42	257	38	48	-496	67	319	70	-6	2698	144	56	-208	71	-374	70	70	212	1251	78	-276	99	.	.	18	100	6	100	90	65	17	73	120	48	61	111	236	68	-123	294	122	64	304	35	151	106	30	272	-51	135	42	206	1	7541	-54	135	-110	112	32	149	-70	132	-379	58	-147	78	-159	100	-85	84	58	57	599	48	380	56	520	50	204	43	-186	146	76	214	116	133	18	1097	-690	58	-263	82	-32	235	.	.	-3146	80
fir	n/a	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.
	living	-139	77	-62	109	25	140	-313	90	52	158	10	2124	436	31	325	128	169	172	-350	108	14	80	16	53	57	56	.	.	84	53	41	197	-220	148	-88	177	4	100	-25	310	85	73	-57	76	9	269	94	85	-17	100	321	73	29	748	223	89	167	120	-7	840	20	452	44	181	10	345	400	37	37	127	23	158	168	45	157	61	-39	95	45	83	218	66	56	238	45	72	26	416	-98	120	-68	71	130	49	229	58	-51	265	12	708	1	6631	38	113	40	96	10	100	81	61	5	100	.	.	.	.	7	100	21	129	16	271	71	99	-53	176	.	.	-37	106	20	564	110	72	170	68	115	58	10	205	100	135	-33	319	-18	607	28	255	79	48	143	41	82	76	-102	77	90	69	-218	109	34	100	37	108	57	62	239	39	65	67	-34	202	-37	234	48	176	8	891	38	89	-5	100	-99	128	.	.	3376	34
	dead	86	60	.	.	.	.	-1	975	2	100	-20	135	86	92	68	109	82	65	156	50	3	97	.	.	12	102	.	.	3	84	-5	82	-5	158	87	78	.	.	2	350	-14	84	67	104	-29	93	25	112	36	100	64	127	2	1007	13	356	135	62	5	530	11	88	13	100	.	.	4	258	9	123	36	101	6	250	-14	165	-2	100	-25	100	-13	100	120	78	.	.	9	473	13	117	63	71	-106	64	-4	104	20	76	14	67	8	100	.	.	.	.	.	.	-2	100	10	100	.	.	.	.	.	.	8	100	31	101	0	100	38	99	.	.	36	60	3	651	-16	101	9	461	0	100	.	.	91	104	0	100	9	100	-19	71	-5	87	9	110	0	100	-5	100	53	73	-3	100	.	.	-6	95	8	122	15	151	30	78	.	.	16	91	-6	503	-5	100	0	100	.	.	.	.	.	.	1317	23
	total	-54	170	-62	109	25	140	-314	89	54	152	-10	2170	522	34	393	103	251	114	-194	190	17	83	16	53	69	55	.	.	87	53	36	230	-225	144	-1	12344	4	100	-23	317	71	89	9	684	-20	232	119	61	20	100	386	69	31	723	236	86	302	59	-2	2371	31	299	57	146	10	345	404	38	45	106	59	98	174	46	143	65	-41	91	21	149	205	71	176	48	45	72	35	265	-85	137	-5	441	24	398	225	58	-31	446	25	326	9	1045	38	113	40	96	10	100	79	62	15	100	.	.	.	.	7	100	29	89	46	76	71	99	-15	588	.	.	-1	2824	23	481	94	89	180	76	115	58	10	205	192	49	-33	319	-8	1330	9	779	74	49	152	38	82	76	-107	73	143	57	-221	108	34	100	31	127	65	54	254	40	95	57	-34	202	-21	422	41	190	3	2375	38	89	-5	100	-99	128	.	.	4693	24
pine	n/a	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.
	living	-50	73	-14	72	-8	110	3	558	.	.	-17	100	-54	123	47	100	-48	105	-18	253	-2	688	58	68	24	58	.	.	3	100	-123	106	.	.	-43	114	-43	59	.	.	36	69	8	442	4	100	34	233	-13	798	14	562	1	100	59	77	.	.	-57	100	2	100	.	.	.	.	20	100	4	100	28	100	26	100	10	100	.	.	.	.	.	.	11	100	-30	163	1	229	-6	165	-2	716	-3	515	20	100	1	100	.	.	-4	402	-41	91	9	299	.	.	-18	194	9	100	.	.	.	.	.	.	.	.	.	.	-3	100	.	.	.	.	41	56	.	.	.	.	.	.	.	.	4	79	0	100	.	.	-8	100	.	.	1	94	.	.	4	100	.	.	.	.	-26	100	.	.	-44	114	30	158	-91	75	.	.	-6	100	16	249	-5	119	-59	95	-16	231	-99	76	11	100	.	.	-418	75
	dead	-19	100	.	.	.	.	.	.	.	.	.	.	16	141	4	100	-6	474	32	64	11	100	.	.	-1	384	.	.	.	.	-39	100	.	.	-28	73	-4	100	.	.	2	267	28	110	.	.	17	74	112	41	-19	62	.	.	.	.	.	.	.	.	0	100	.	.	.	.	-3	100	.	.	1	100	6	100	.	.	.	.	.	.	.	.	.	.	23	63	.	.	0	100	-6	150	6	159	0	100	.	.	.	.	16	100	.	.	-4	100	.	.	2	91	0	100	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	5	100	-2	100	.	.	.	.	.	.	-10	100	.	.	.	.	-1	100	.	.	8	100	.	.	.	.	.	.	.	.	26	100	.	.	28	87	16	109	45	84	.	.	37	100	15	95	-5	92	12	100	.	.	-10	100	.	.	.	.	309	37
	total	-69	60	-14	72	-8	110	3	558	.	.	-17	100	-37	127	51	100	-54	84	13	336	9	88	58	68	23	50	.	.	3	100	-162	104	.	.	-71	77	-48	60	.	.	37	75	35	106	4	100	51	149	99	97	-5	1375	1	100	59	77	.	.	-57	100	2	100	.	.	.	.	16	100	4	100	29	100	32	100	10	100	.	.	.	.	.	.	11	100	-7	655	1	229	-6	166	-8	278	3	374	20	100	1	100	.	.	12	65	-41	91	5	547	.	.	-16	220	9	100	.	.	.	.	.	.	.	.	.	.	-3	100	.	.	.	.	46	54	-2	100	.	.	.	.	.	.	-7	161	0	100	.	.	-9	100	.	.	8	100	.	.	4	100	.	.	.	.	0	100	.	.	-16	288	46	101	-46	109	.	.	31	100	31	130	-10	81	-46	118	-16	231	-109	70	11	100	.	.	-109	295
larch	n/a	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.
	living	16	160	-21	91	39	115	-50	76	.	.	.	.	19	120	-16	100	-60	107	.	.	.	.	.	.	2	94	.	.	.	.	11	100	.	.	14	73	.	.	-16	72	-30	254	22	200	41	80	145	55	154	175	2	100	1	100	8	71	1	100	.	.	.	.	.	.	-2	100	.	.	.	.	.	.	4	100	2	100	7	100	11	247	0	100	-10	100	-3	381	.	.	.	.	3	100	.	.	.	.	.	.	6	100	5	100	-17	100	27	100	-22	157	39	135	115	53	26	118	.	.	0	1944	336	36	28	104	39	150	.	.	.	.	.	.	62	70	.	.	10	100	.	.	20	100	.	.	10	100	.	.	.	.	-12	100	.	.	8	113	.	.	11	100	.	.	39	100	206	72	234	67	-51	124	-15	100	8	100	-6	100	19	88	.	.	-28	71	5	100	1	1636	.	.	1395	31
	dead	.	.	.	.	.	.	.	.	.	.	.	.	-1	110	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	-28	100	.	.	-3	100	.	.	.	.	48	91	0	3075	28	72	49	74	123	84	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	1	100	.	.	5	100	-3	78	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	7	100	.	.	-1	102	6	341	-1	101	-1	100	.	.	.	.	18	65	0	100	13	157	.	.	.	.	.	.	13	103	.	.	4	100	.	.	.	.	.	.	.	.	.	.	.	.	-12	100	.	.	-8	100	.	.	.	.	.	.	1	100	-21	182	-7	192	4	822	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	234	59
	total	16	160	-21	91	39	115	-50	76	.	.	.	.	18	125	-16	100	-60	107	.	.	.	.	.	.	2	94	.	.	.	.	-16	184	.	.	12	94	.	.	-16	72	18	197	22	221	69	73	195	41	277	89	2	100	1	100	8	71	1	100	.	.	.	.	.	.	-2	100	.	.	.	.	.	.	5	100	2	100	12	100	8	331	0	100	-10	100	-3	381	.	.	.	.	3	100	.	.	.	.	.	.	6	100	5	100	-9	100	27	100	-22	151	45	99	114	54	24	122	.	.	0	1944	354	35	28	104	51	96	.	.	.	.	.	.	75	56	.	.	14	100	.	.	20	100	.	.	10	100	.	.	.	.	-24	100	.	.	0	2841	.	.	11	100	.	.	41	100	185	79	226	70	-47	141	-15	100	8	100	-6	100	19	88	.	.	-28	71	5	100	1	1636	.	.	1630	25
Arolla pine	n/a	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.
	living	.	.	.	.	.	.	.	.	.	.	.	.	19	100	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	1	100	.	.	.	.	13	239	143	63	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	3	100	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	93	44	-32	85	-10	100	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	230	48
	dead	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	6	271	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	16	90	9	73	-2	100	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	29	77
	total	.	.	.	.	.	.	.	.	.	.	.	.	19	100	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	1	100	.	.	.	.	13	239	148	62	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	3	100	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	108	38	-23	110	-12	100	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	258	43
other conifers	n/a	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.
	living	6	72	.	.	28	100	43	75	.	.	5	71	0	100	.	.	159	42	1	71	.	.	.	.	.	.	75	.	.	.	.	.	.	.	.	.	.	.	0	100	-1	100	.	.	.	.	-1	100	-2	119	16	90	16	94	77	79	1	100	.	.	.	.	0	100	.	.	.	.	.	.	.	.	4	100	50	92	24	88	-3	124	0	838	.	.	9	100	2	100	25	100	18	85	.	.	.	.	.	.	1	100	.	.	.	.	0	86	.	.	.	.	.	.	.	.	.	.	.	.	31	100	1	100	.	.	.	.	.	.	1	100	.	.	3	100	.	.	.	.	-47	100	10	62	.	.	1	100	.	.	.	.	.	.	-185	100	.	.	4	100	.	.	.	.	-2	73	-1	100	1	77	.	.	.	.	5	55	14	123	3	72	.	.	.	.	.	.	.	.	393	61
	dead	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	4	100	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	1	100	.	.	.	.	2	100	2	127	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	3	100	.	.	.	.	.	.	.	.	-2	100	-1	174	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	2	100	0	100	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	11	60
	total	6	72	.	.	28	100	43	75	.	.	5	71	0	100	.	.	163	41	1	71	.	.	.	.	.	.	75	.	.	.	.	.	.	.	.	.	.	.	0	100	0	100	.	.	.	.	1	100	0	608	16	90	16	94	77	79	1	100	.	.	.	.	0	100	.	.	.	.	.	.	.	.	4	100	50	92	24	88	-3	124	0	838	.	.	9	100	2	100	25	100	18	85	.	.	.	.	.	.	1	100	.	.	.	.	0	86	.	.	.	.	.	.	.	.	.	.	.	.	31	100	1	100	.	.	.	.	.	.	4	100	.	.	3	100	.	.	.	.	-49	100	9	60	.	.	1	100	.	.	.	.	.	.	-185	100	.	.	4	100	.	.	.	.	-2	73	2	100	1	112	.	.	.	.	5	55	14	123	3	72	.	.	.	.	.	.	.	.	404	59
beech	n/a	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.
	living	-225	92	2	4858	37	209	-261	60	64	98	-63	113	-108	258	391	60	-161	179	53	375	-94	70	-99	173	-209	72	.	.	24	153	-8	1524	49	279	-2	7437	.	.	-26	421	-5	1074	14	466	-9	96	61	73	.	.	-178	120	70	194	29	323	100	59	-146	96	-48	71	62	96	-7	884	-94	124	50	135	18	64	-190	52	223	52	-74	276	218	53	-128	144	57	270	51	195	80	140	-265	60	-169	102	-70	147	18	295	57	71	117	57	34	216	-54	89	31	378	.	.	51	70	.	.	77	52	125	73	126	49	278	49	177	44	81	102	125	77	.	.	27	162	37	134	-56	106	41	133	156	51	-3	529	27	184	37	89	-29	104	27	162	-27	265	-169	78	38	229	15	255	58	53	-14	667	-54	85	.	.	9	82	-45	185	65	52	84	37	97	58	8	1018	-26	426	39	191	-97	69	25	183	.	.	527	191
	dead	121	75	-10	283	.	.	60	70	2	99	24	73	31	180	-34	102	9	675	60	81	23	208	29	71	52	69	.	.	9	304	-15	197	34	71	-5	439	.	.	46	50	48	79	-1	215	2	100	24	78	.	.	27	169	-8	231	4	81	-15	485	50	73	-1	100	.	.	.	.	-3	100	8	104	8	100	7	147	6	100	58	60	44	64	2	508	34	61	30	56	-1	2868	-31	159	34	110	85	45	2	100	41	102	11	106	-2	100	.	.	-3	155	.	.	.	.	.	.	-6	281	11	270	-6	302	2	775	55	54	-38	87	7	86	.	.	.	.	7	242	.	.	2	122	5	100	0	100	89	56	2	74	3	100	0	100	14	93	1	315	-2	252	17	94	.	.	5	100	.	.	.	.	.	.	69	56	-5	100	-7	100	.	.	30	83	-19	80	-7	85	6	100	-6	100	.	.	1126	21
	total	-104	186	-8	1210	37	209	-201	61	66	95	-39	154	-77	344	357	65	-152	184	113	169	-71	126	-70	229	-158	100	.	.	33	62	-23	562	83	167	-7	2377	.	.	20	509	43	142	13	496	-7	96	85	59	.	.	-150	140	63	214	33	283	85	102	-96	114	-49	71	62	96	-7	884	-97	123	57	113	26	59	-184	52	229	51	-17	1277	261	50	-126	150	91	167	81	124	80	151	-296	53	-136	126	14	629	20	263	98	48	129	58	33	227	-54	89	28	424	.	.	51	70	.	.	70	64	136	59	120	53	280	48	231	35	44	150	132	73	.	.	27	162	44	97	-56	106	43	128	161	51	-3	530	116	40	39	87	-25	117	27	164	-13	503	-168	79	36	246	32	123	58	53	-9	1060	-54	85	.	.	9	82	24	306	61	59	77	40	97	58	38	206	-45	254	32	242	-91	72	20	238	.	.	1653	60
maple	n/a	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.
	living	94	44	51	57	-55	63	-37	68	7	99	22	210	-4	2611	139	42	190	31	117	48	12	253	16	142	-43	63	.	.	-14	146	29	57	32	116	35	67	.	.	52	131	25	128	41	76	20	86	3	443	3	100	62	114	45	69	-17	134	-5	750	23	93	10	125	37	96	58	73	11	59	7	499	11	84	-60	59	-13	305	196	78	49	99	22	148	125	36	15	94	52	47	28	84	24	86	100	79	-20	269	11	189	35	80	50	76	-47	156	31	113	23	100	15	100	-8	100	4	64	-26	71	-1	1336	4	65	29	93	8	60	5	391	12	81	1	100	-5	441	-12	127	53	111	10	126	9	78	23	94	10	100	16	82	7	113	35	96	-6	439	29	71	25	76	-6	100	.	.	64	69	8	100	15	68	91	46	-5	451	36	96	35	96	53	100	9	270	42	120	-62	77	13	227	.	.	2130	17
	dead	0	100	-2	100	.	.	-1	204	.	.	16	103	14	117	.	.	-3	300	12	87	9	74	7	100	2	100	.	.	.	.	2	100	.	.	-10	100	.	.	-1	1486	.	.	.	.	-2	100	.	.	.	.	23	99	0	100	13	77	-1	250	6	100	.	.	-1	100	.	.	.	.	11	114	.	.	.	.	.	.	-23	73	13	81	.	.	-10	100	0	100	.	.	1	100	.	.	.	.	1	188	.	.	.	.	.	.	17	100	.	.	.	.	.	.	.	.	.	.	14	100	0	100	.	.	.	.	.	.	1	100	.	.	.	.	-2	100	4	75	-3	100	.	.	.	.	.	.	.	.	.	.	.	.	.	.	-2	100	3	204	.	.	.	.	.	.	.	.	.	.	.	.	-13	96	.	.	.	.	-2	100	-14	79	-8	100	-3	100	.	.	6	100	.	.	71	83
	total	94	44	49	59	-55	63	-38	65	7	99	38	113	11	845	139	42	186	31	130	41	21	161	23	82	-41	65	.	.	-14	146	30	54	32	116	25	103	.	.	51	137	25	128	41	76	19	94	3	443	3	100	85	81	45	69	-4	587	-7	594	30	91	10	125	37	96	58	73	11	59	19	193	11	84	-60	59	-13	305	173	89	62	76	22	148	115	35	15	94	52	47	29	80	24	86	100	79	-20	277	11	189	35	80	50	76	-30	257	31	113	23	100	15	100	-8	100	4	64	-12	87	-1	1027	4	65	29	93	8	60	6	308	12	81	1	100	-7	300	-8	183	51	116	10	126	9	78	23	94	10	100	16	82	7	113	35	96	-8	307	32	68	25	76	-6	100	.	.	64	69	8	100	15	68	78	47	-5	451	36	96	33	101	39	138	1	3643	40	123	-62	77	18	163	.	.	2201	16
ash	n/a	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.
	living	-16	311	-35	117	-138	64	-85	99	.	.	-81	113	-50	73	-60	161	-19	370	-32	109	-142	55	-10	200	9	140	.	.	-32	136	48	236	149	52	-111	80	-19	100	-22	246	14	76	3	440	-16	377	15	41	.	.	-152	60	-195	92	-99	56	-60	64	-5	184	-26	77	2	100	-2	141	2	100	72	129	.	.	49	86	63	193	-41	236	1	1059	-60	161	-50	100	16	158	36	57	3	398	-78	72	-2	622	6	536	7	91	-30	111	-137	89	-167	59	18	317	6	100	88	100	2	100	-1	527	-3	581	47	78	48	60	-45	64	22	57	28	128	3	247	.	.	-103	80	25	53	10	243	149	80	45	93	-17	87	-70	100	7	90	3	100	10	84	-24	128	-21	148	17	61	-165	77	.	.	-167	109	12	164	16	56	52	68	-56	131	47	87	-74	74	-60	86	-23	289	27	151	-43	68	-51	68	.	.	-1716	33
	dead	17	89	43	71	2	100	3	100	.	.	36	68	38	93	38	75	28	93	4	71	23	85	12	100	.	.	.	.	1	100	30	80	0	1956	27	105	1	100	84	59	.	.	.	.	23	86	-8	100	.	.	232	51	6	87	3	285	44	71	-2	100	.	.	.	.	.	.	.	.	38	76	.	.	6	100	58	46	0	20398	.	.	20	100	32	68	11	68	.	.	.	.	13	78	3	172	17	172	.	.	5	100	0	1490	38	100	18	100	-3	100	.	.	.	.	.	.	4	100	1	100	2	551	30	100	-9	100	3	100	.	.	.	.	-5	347	8	66	4	100	11	88	.	.	.	.	.	.	.	.	.	.	.	.	-3	225	12	71	.	.	-9	100	.	.	.	.	0	100	0	100	2	499	.	.	.	.	18	74	-5	374	20	106	.	.	2	71	-3	100	.	.	1023	18
	total	1	6425	8	662	-136	65	-82	99	.	.	-45	169	-12	271	-22	401	9	702	-28	125	-119	58	3	523	9	140	.	.	-30	138	78	144	149	52	-84	101	-18	100	61	84	14	76	3	440	7	702	7	120	.	.	79	167	-190	95	-96	58	-16	218	-7	157	-26	77	2	100	-2	141	2	100	110	80	.	.	55	76	121	98	-41	220	1	1059	-40	261	-18	214	27	91	36	57	3	398	-65	82	0	3766	23	129	7	91	-25	123	-138	89	-129	86	36	120	4	100	88	100	2	100	-1	527	1	1717	48	77	50	75	-14	105	13	100	30	124	3	247	.	.	-109	85	34	49	14	157	160	76	45	93	-17	87	-70	100	7	90	3	100	10	84	-27	131	-9	365	17	61	-174	77	.	.	-167	109	12	163	15	56	55	64	-56	131	47	87	-56	96	-65	87	-3	2651	27	151	-41	71	-54	62	.	.	-693	83
oak	n/a	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.
	living	61	64	17	66	.	.	20	61	.	.	.	.	1	71	8	106	-45	207	.	.	0	100	1	100	-9	91	.	.	1	100	6	100	18	89	46	54	-88	155	.	.	.	.	5	100	.	.	.	.	14	100	33	175	-4	126	-3	260	4	100	2	295	.	.	2	100	-2	100	.	.	0	100	.	.	.	.	-4	100	25	79	.	.	-6	282	.	.	-31	122	13	100	-9	112	13	77	-6	645	3	100	.	.	.	.	-10	187	66	105	13	282	.	.	.	.	.	.	1	1510	3	754	29	196	-17	69	10	316	19	83	6	330	.	.	5	100	0	73	-1	100	.	.	37	95	2	100	5	71	-47	112	-13	157	.	.	-2	987	5	100	-16	76	-22	138	-25	100	17	100	17	85	19	84	19	50	17	79	.	.	-35	116	9	64	5	100	-28	194	21	83	-72	87	11	84	.	.	130	199
	dead	3	100	.	.	.	.	.	.	.	.	.	.	1	100	21	100	2	250	.	.	.	.	.	.	-4	71	.	.	0	100	.	.	-1	100	.	.	-31	86	.	.	.	.	.	.	.	.	0	100	.	.	-6	311	-21	124	.	.	.	.	8	85	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	2	100	.	.	.	.	.	.	-3	86	.	.	11	99	.	.	16	62	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	13	83	2	100	31	109	6	80	23	61	.	.	9	100	.	.	.	.	-2	100	0	100	.	.	.	.	.	.	.	.	-10	100	.	.	.	.	1	81	.	.	-7	100	26	70	.	.	.	.	.	.	1	100	0	1120	-2	165	.	.	.	.	.	.	.	.	.	.	2	100	.	.	0	100	.	.	92	73
	total	65	61	17	66	.	.	20	61	.	.	.	.	1	78	29	78	-43	215	.	.	0	100	1	100	-12	77	.	.	1	100	6	100	16	97	46	54	-119	132	.	.	.	.	5	100	.	.	0	100	14	100	27	225	-25	105	-3	260	4	100	10	72	.	.	2	100	-2	100	.	.	0	100	.	.	.	.	-4	100	27	75	.	.	-6	282	.	.	-34	113	13	100	2	71	13	77	11	286	3	100	.	.	.	.	-10	187	66	105	13	282	.	.	.	.	.	.	14	85	5	432	59	78	-11	80	33	77	19	83	15	107	.	.	5	100	-2	89	-1	100	.	.	37	95	2	100	5	71	-57	110	-13	157	.	.	-1	2172	5	100	-22	74	4	793	-25	100	17	100	17	85	20	84	19	48	15	92	.	.	-35	116	9	64	5	100	-28	194	23	73	-72	87	10	86	.	.	222	122
sweet chestnut	n/a	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.
	living	.	.	.	.	-6	100	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	5	100	.	.	.	.	63	58	-1	163	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	1	100	87	64	43	67	-12	503	-91	83	63	193	43	136	-76	70	-57	233	.	.	.	.	.	.	.	.	-1	100	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	-2	100	.	.	.	.	.	.	.	.	5	100	.	.	2	140	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	65	358
	dead	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	17	89	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	0	100	30	58	11	85	42	53	55	82	96	37	27	59	11	97	100	40	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	-2	100	.	.	.	.	.	.	.	.	-1	100	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	384	20
	total	.	.	.	.	-6	100	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	5	100	.	.	.	.	79	55	-1	163	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	1	100	116	58	54	67	29	210	-36	146	158	73	70	87	-66	77	43	305	.	.	.	.	.	.	.	.	-1	100	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	-3	71	.	.	.	.	.	.	.	.	4	100	.	.	2	140	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	449	50
other broadleaves	n/a	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.
	living	-11	312	78	41	0	21799	10	151	-3	100	12	87	-73	88	60	78	-82	143	12	102	8	344	14	156	1	1752	.	.	5	121	-125	127	24	55	59	49	4	79	-32	129	-19	119	-9	186	10	612	-147	58	87	148	94	68	5	617	-2	541	36	74	-2	100	4	129	0	100	-25	62	-24	108	9	319	-9	78	17	62	-3	100	1	1600	-12	181	-101	114	12	241	3	216	52	112	-57	70	49	60	3	74	29	84	1	334	22	74	25	349	19	189	-2	533	-29	72	256	58	9	122	16	122	24	155	255	44	-8	598	-71	122	74	81	0	2209	-33	100	8	62	-118	72	31	103	2	159	8	193	70	95	-30	126	-2	239	-2	160	-2	412	30	76	-1	132	-6	80	-5	137	0	3813	2	100	1	100	-5	963	20	188	62	96	0	3512	9	207	56	78	-2	635	13	62	11	109	-16	172	40	81	.	.	695	64
	dead	9	165	-2	269	.	.	-11	92	-1	100	4	96	7	257	33	69	.	.	0	100	26	94	8	100	-4	127	.	.	-12	87	60	100	0	1027	5	235	-1	100	36	103	1	855	-14	70	-7	705	51	97	78	85	23	149	-1	725	7	113	-8	57	.	.	3	100	3	100	-1	100	17	100	-4	100	-10	119	-7	62	3	100	-5	58	13	125	39	77	11	117	-3	100	.	.	20	100	9	103	-1	100	-38	82	.	.	2	152	13	116	2	100	.	.	21	62	0	16051	0	606	-7	268	14	159	25	132	-49	61	33	84	-17	158	0	341764	6	100	-2	100	29	87	24	81	-9	89	3	197	-6	109	-8	237	2	100	8	103	0	100	.	.	-2	206	10	94	4	100	-15	102	-1	100	.	.	-8	214	16	81	30	54	-1	100	-4	100	0	100	-3	474	-3	100	-2	100	-11	125	-3	100	.	.	424	40
	total	-3	1601	76	43	0	21799	-1	1308	-4	77	16	63	-66	99	94	43	-82	143	12	100	34	51	22	131	-3	530	.	.	-7	93	-65	166	23	56	64	49	3	124	4	369	-18	123	-24	96	4	2117	-96	70	165	67	117	81	4	709	6	247	28	97	-2	100	6	53	3	100	-26	60	-7	127	4	578	-19	98	10	103	0	1151	-4	286	1	1529	-63	183	23	138	0	19050	52	112	-37	62	58	53	2	143	-10	380	1	334	24	70	38	238	21	169	-2	533	-8	161	256	61	9	111	8	358	38	110	281	45	-57	118	-38	197	57	93	0	2393	-27	100	5	102	-89	70	55	92	-7	88	11	177	63	106	-37	109	0	5259	6	88	-3	366	30	76	-2	123	4	123	-1	339	-15	186	1	100	1	100	-13	326	36	89	91	63	-1	442	5	314	57	77	-5	274	10	80	8	138	-26	112	37	88	.	.	1119	39
indeterminable	n/a	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.
	living	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.
	dead	-4	100	.	.	.	.	.	.	.	.	0	254	-16	77	3	123	-5	100	0	100	-1	100	.	.	0	100	.	.	-1	100	-1	100	.	.	-2	100	.	.	-9	100	10	76	13	120	15	156	-2	164	0	88	13	100	4	158	-2	100	-19	85	.	.	.	.	.	.	15	100	-1	100	35	72	-5	100	1	100	4	100	0	100	2	100	3	100	3	380	.	.	.	.	-6	91	.	.	.	.	-13	100	.	.	.	.	.	.	0	849	.	.	.	.	.	.	.	.	.	.	.	.	-3	213	0	100	-11	100	.	.	0	100	.	.	-2	100	-7	82	2	122	1	224	-3	100	.	.	-1	100	.	.	.	.	1	100	2	100	.	.	.	.	-1	100	.	.	.	.	.	.	16	97	1	152	-3	69	.	.	.	.	.	.	.	.	7	100	0	100	.	.	0	100	.	.	32	182
	total	-4	100	.	.	.	.	.	.	.	.	0	254	-16	77	3	123	-5	100	0	100	-1	100	.	.	0	100	.	.	-1	100	-1	100	.	.	-2	100	.	.	-9	100	10	76	13	120	15	156	-2	164	0	88	13	100	4	158	-2	100	-19	85	.	.	.	.	.	.	15	100	-1	100	35	72	-5	100	1	100	4	100	0	100	2	100	3	100	3	380	.	.	.	.	-6	91	.	.	.	.	-13	100	.	.	.	.	.	.	0	849	.	.	.	.	.	.	.	.	.	.	.	.	-3	213	0	100	-11	100	.	.	0	100	.	.	-2	100	-7	82	2	122	1	224	-3	100	.	.	-1	100	.	.	.	.	1	100	2	100	.	.	.	.	-1	100	.	.	.	.	.	.	16	97	1	152	-3	69	.	.	.	.	.	.	.	.	7	100	0	100	.	.	0	100	.	.	32	182
total	n/a	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.
	living	-296	102	4	6099	-13	1124	-1296	41	362	64	-891	64	-375	247	-234	340	-981	87	-875	63	-162	93	-26	789	-158	114	75	.	32	403	-482	99	-127	481	418	74	-138	105	-733	63	560	63	492	69	13	3831	470	117	439	115	-321	174	-257	163	135	255	-903	81	-263	69	177	82	-4	3319	50	255	166	162	408	49	195	58	509	66	818	35	261	163	362	113	-183	214	-115	388	-426	69	199	125	-651	54	-253	96	181	91	-189	182	218	117	104	231	101	219	-409	66	-368	95	37	454	1744	59	-369	96	109	73	51	256	533	35	814	27	84	173	375	55	148	136	183	80	-83	398	20	1102	371	41	310	84	463	41	59	219	149	118	-54	417	-134	139	-74	216	148	82	-173	108	-465	71	-208	87	-159	148	-340	100	-1	31776	682	48	445	79	652	51	247	51	-258	145	145	176	200	131	-81	352	-550	78	-659	47	-57	295	.	.	-76	4478
	dead	185	63	10	401	-17	265	68	102	16	127	189	58	103	242	187	86	160	70	580	36	78	86	65	56	56	79	.	.	-36	145	-114	112	-227	101	85	101	-36	76	156	70	83	129	100	96	464	55	376	37	605	35	588	36	27	277	40	170	177	127	73	60	34	68	26	72	56	79	130	93	105	38	-1	5366	164	53	37	112	54	111	64	142	39	136	250	47	250	71	1	3445	-4	1004	113	48	12	655	-60	136	188	53	86	50	42	58	61	86	172	62	41	55	142	95	291	48	39	81	99	64	143	45	26	147	174	37	47	143	82	56	42	60	44	146	28	217	52	117	136	76	59	75	-18	68	182	64	-46	109	54	50	9	302	4	644	55	64	21	159	29	64	-4	1705	43	72	-6	248	271	43	347	39	279	47	36	75	207	77	79	78	-9	525	2	1677	-15	184	-6	309	-31	82	.	.	8789	10
	total	-111	255	14	1742	-30	457	-1229	40	378	64	-702	78	-272	348	-47	1703	-821	103	-295	176	-84	167	39	525	-102	187	75	.	-4	2945	-596	88	-354	215	503	60	-174	96	-577	81	643	58	593	59	477	83	846	61	1044	44	268	239	-230	178	175	200	-725	97	-190	77	211	70	22	565	106	119	296	95	513	40	194	68	673	59	855	34	316	136	426	95	-145	277	135	307	-176	129	200	123	-655	53	-141	166	193	87	-248	156	406	73	189	128	142	156	-347	79	-195	168	77	216	1886	61	-78	363	149	57	150	76	676	29	840	27	258	57	421	46	230	91	224	71	-39	928	48	440	423	38	446	70	522	43	41	319	330	49	-100	261	-80	235	-65	238	152	79	-118	155	-444	75	-179	101	-163	173	-297	114	-7	3641	953	37	792	40	931	34	284	47	-51	671	224	113	191	142	-80	366	-566	75	-665	46	-88	193	.	.	8713	40

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. 2296627. Birmensdorf, Swiss Federal Research Institute WSL

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