Selection from the list of topics

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

1. What do the numbers stand for?

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

Example 1: Estimated value and standard error

NFI5

volume of deadwood (stemwood)
ownership (2 categories)

regional demarcation: production region

unit: m³/ha

evaluation area: accessible forest without shrub forest

grid: 1.4 km grid, subgrids 1-5

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

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

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2. What is the purpose of the standard error?

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

The statistical certainty is:

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

Example 2: Calculating confidence intervals

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

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

Procedure

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

Answer

			Step 1	Step 2

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

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

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

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

Data: see example 2

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

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

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3. When are two results statistically different?*

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

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

Example 4: Interpretation of two results from the same inventory

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

	case 2						case 1

case 1

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

Procedure

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

Answer

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

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

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

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

Case 2

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

Procedure

See case 1.

Answer

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

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

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

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

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

Example 5: Interpretation of two results from different inventories

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

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

Procedure

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

Answer

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

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

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

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

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

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

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

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

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

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

Procedure

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

Answer

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

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

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

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

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

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

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

Procedure

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

Answer

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

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

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

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

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

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

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

Example 8: Standard error and combination of variable expressions

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

The standard error increases as the level of detail increases.

Large standard errors are to be expected if:

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

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

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

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5. Two types of changes?

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

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

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

The results are:

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

Example 9: : Additivity/non-additivity of changes

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

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

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

Example 10: Average number of years per domain

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

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

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

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

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

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

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

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

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

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

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NFI4
total number of stems with two most important forms of damages
slope (in 20% classes) · cause of damage to trees (10 classes)
regional demarcation: forest district (2024)
unit: n/ha
evaluation area: accessible forest without shrub forest NFI1-NFI5
grid: 1.4 km grid, subgrids 1-5
state 2009/17
		forest district (2024)
		AG01		AG02		AG03		AG04		AI01		AR01		BE01		BE02		BE03		BE04		BSBL01		BSBL02		BSBL03		BSBL04		FR01		FR02		FR03		FR04		GE01		GL01		GR01		GR02		GR03		GR04		GR05		JU01		LU01		LU02		LU03		NE01		NE02		NE03		NE04		NE06		NW01		OW01		OW02		SG01		SG02		SG03		SG04		SG05		SH01		SO01		SO02		SO03		SO04		SZ01		SZ02		SZ03		TG01		TG02		TG03		TI01		TI02		TI03		TI04		TI05		TI06		TI07		TI08		TI09		UR01		UR02		UR03		VD02		VD03		VD04		VD05		VD06		VD07		VD08		VD09		VD11		VD12		VD14		VD15		VD16		VD18		VD20		VD22		VS01		VS02		VS03		ZG01		ZH01		ZH02		ZH03		ZH04		ZH05		ZH06		ZH07		lakes		Switzerland
slope (in 20% classes)	cause of damage to trees (10 classes)	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	.
	no visible damage	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	fire	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	rockfall	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	various	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	indeterminable	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	wood harvest	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	other human activity	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	weather	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	lying living trees	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	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 trees	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	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	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.
to 20%	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	.
	no visible damage	310	24	240	25	461	15	245	19	330	.	498	24	459	26	299	16	304	10	346	18	94	54	248	15	322	22	190	.	282	34	328	24	543	27	345	20	334	25	305	.	230	26	378	21	328	70	195	34	537	20	288	14	436	25	421	15	625	11	516	28	343	26	274	15	435	12	291	19	390	.	279	33	850	33	318	19	246	60	174	10	473	15	240	23	359	15	305	22	199	18	144	26	402	40	363	8	516	28	158	22	451	23	415	17	379	16	100	.	0	.	240	.	220	.	660	.	0	.	0	.	0	.	0	.	0	.	640	.	0	.	380	.	804	34	0	.	406	38	338	36	332	19	257	37	274	44	349	13	492	19	612	31	300	18	533	37	282	26	521	.	409	28	631	39	435	32	142	4	292	28	244	20	282	21	272	20	272	8	279	20	248	22	341	21	0	.	340	3
	fire	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	2	96	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	10	71	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	71
	rockfall	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	1	97	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	100
	various	0	.	0	.	6	96	0	.	0	.	10	50	10	64	2	98	8	64	46	63	6	83	17	52	12	87	0	.	20	74	4	96	0	.	2	67	0	.	0	.	4	89	7	93	25	70	0	.	33	92	6	45	4	96	6	57	6	82	5	87	0	.	0	.	36	53	10	53	0	.	0	.	0	.	2	96	0	.	0	.	7	85	3	91	0	.	11	62	0	.	0	.	16	84	0	.	0	.	29	60	6	70	1	97	2	98	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	51	39	0	.	7	93	0	.	2	95	4	90	0	.	14	43	0	.	17	57	2	96	36	64	0	.	0	.	11	67	0	.	0	.	0	.	0	.	0	.	4	64	14	55	2	96	8	56	7	46	4	96	0	.	7	16
	indeterminable	30	31	28	33	35	24	13	42	40	.	5	87	31	28	27	29	31	14	19	45	13	43	40	35	0	.	0	.	79	34	27	61	36	50	37	35	37	65	0	.	22	53	68	55	50	70	0	.	122	45	43	25	31	33	39	35	35	58	45	44	65	67	36	46	41	56	23	33	0	.	11	89	0	.	43	45	7	83	20	69	77	69	15	49	38	48	18	52	30	24	24	49	85	84	80	66	22	78	58	60	33	65	36	32	21	40	0	.	0	.	137	.	150	.	50	.	0	.	0	.	0	.	50	.	0	.	200	.	0	.	0	.	42	64	0	.	40	53	11	41	42	51	34	41	0	.	16	36	27	48	37	47	40	31	42	33	10	75	0	.	16	93	43	51	30	24	0	.	17	58	27	41	34	37	26	35	28	38	37	37	49	44	20	36	0	.	32	6
	wood harvest	12	50	0	.	8	79	23	45	0	.	0	.	0	.	12	45	13	25	13	71	0	.	28	53	47	48	0	.	14	72	6	71	0	.	17	41	0	.	0	.	0	.	0	.	0	.	50	71	0	.	20	42	27	52	17	48	0	.	0	.	16	59	16	42	5	89	8	64	0	.	0	.	0	.	2	96	0	.	0	.	0	.	23	62	20	47	7	94	25	69	6	95	0	.	0	.	0	.	0	.	9	96	7	66	15	61	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	15	65	7	91	3	93	8	93	0	.	4	75	0	.	0	.	22	69	0	.	7	65	221	.	0	.	0	.	0	.	0	.	11	89	17	91	13	69	12	60	10	62	5	73	2	94	4	96	0	.	11	10
	other human activity	2	96	0	.	0	.	0	.	0	.	0	.	5	92	10	71	3	66	1	97	0	.	0	.	0	.	20	.	0	.	0	.	0	.	1	97	8	90	0	.	4	89	10	92	0	.	0	.	17	91	3	75	1	96	5	58	0	.	5	87	8	93	0	.	14	86	19	75	0	.	3	95	0	.	14	67	0	.	0	.	35	80	0	.	3	97	0	.	10	69	0	.	0	.	0	.	0	.	0	.	0	.	0	.	2	98	20	.	0	.	34	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	7	94	0	.	12	62	0	.	0	.	3	97	7	93	4	92	0	.	0	.	0	.	0	.	0	.	0	.	25	71	0	.	0	.	3	91	4	95	4	95	0	.	0	.	5	62	4	96	0	.	3	18
	weather	0	.	0	.	0	.	4	73	0	.	0	.	4	90	4	83	8	26	0	.	0	.	23	77	0	.	0	.	7	93	8	96	0	.	1	98	4	90	0	.	0	.	0	.	76	70	0	.	17	58	5	58	2	96	5	97	12	89	0	.	0	.	0	.	0	.	0	.	0	.	7	95	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	6	96	0	.	2	98	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	17	58	0	.	0	.	16	84	0	.	0	.	0	.	9	64	10	89	0	.	39	.	3	93	0	.	0	.	0	.	13	86	3	91	0	.	0	.	0	.	0	.	0	.	0	.	0	.	3	16
	lying living trees	0	.	0	.	0	.	3	97	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	7	92	25	70	0	.	8	92	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	7	95	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	10	95	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	8	91	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	6	94	0	.	0	.	1	37
	dead trees	15	52	16	43	0	.	18	39	0	.	47	87	4	90	18	33	14	26	21	35	23	50	33	68	30	69	0	.	60	93	28	63	19	47	29	32	58	35	0	.	21	53	64	51	0	.	0	.	21	46	30	32	14	45	21	33	50	33	49	38	23	93	20	55	14	86	22	48	0	.	88	71	50	0	15	50	23	50	20	72	15	85	9	91	13	56	6	94	25	69	2	95	43	55	23	75	28	64	0	.	22	77	15	79	14	54	0	.	0	.	0	.	0	.	250	.	0	.	0	.	0	.	0	.	0	.	200	.	0	.	0	.	9	77	0	.	0	.	75	58	13	93	45	90	6	84	20	34	35	62	25	42	49	52	10	90	24	54	0	.	18	44	63	33	25	71	0	.	11	89	38	36	17	48	13	45	0	.	31	30	9	94	26	37	0	.	22	8
	total	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.
21-40 %	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	.
	no visible damage	171	26	306	27	153	28	221	18	418	23	553	15	313	18	293	10	330	10	387	10	215	22	229	29	324	24	0	.	404	24	470	18	177	25	314	24	0	.	347	11	275	18	228	46	314	33	274	26	376	12	355	12	316	19	314	12	477	11	294	17	440	11	430	16	290	27	459	28	529	34	581	32	390	25	386	40	364	43	141	15	238	24	303	20	332	18	368	20	300	32	297	56	369	21	422	23	366	19	301	19	336	26	307	22	234	28	0	.	429	32	344	26	0	.	172	46	526	24	474	41	324	9	546	24	0	.	394	23	400	.	498	15	156	26	788	38	622	29	450	.	400	28	0	.	225	47	347	17	397	40	318	12	343	31	447	49	846	.	155	41	170	.	328	33	351	18	336	31	435	15	300	20	213	22	406	41	281	12	333	25	387	27	328	41	0	.	344	3
	fire	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	6	95	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	100
	rockfall	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	5	98	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	13	86	0	.	0	.	0	.	0	.	0	.	3	91	0	.	0	.	0	.	0	.	0	.	0	.	0	.	26	89	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	5	95	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	1	53
	various	3	66	0	.	4	91	7	56	13	71	5	95	7	48	3	63	4	46	5	69	5	90	0	.	0	.	0	.	0	.	5	70	8	48	3	91	0	.	10	69	10	59	0	.	31	75	18	71	8	49	9	63	24	65	6	74	13	57	6	93	16	68	0	.	10	90	13	85	38	34	0	.	36	55	0	.	0	.	67	86	14	85	7	73	6	71	5	95	0	.	0	.	8	91	13	60	0	.	16	89	11	63	0	.	5	88	0	.	0	.	7	91	0	.	5	85	0	.	10	89	17	82	24	74	0	.	0	.	0	.	0	.	5	86	0	.	23	75	0	.	23	91	0	.	0	.	0	.	0	.	2	96	21	66	0	.	0	.	0	.	0	.	2	96	15	67	0	.	41	64	8	91	0	.	0	.	0	.	7	82	0	.	5	87	0	.	7	12
	indeterminable	36	40	32	45	14	90	11	55	44	40	64	25	40	22	24	21	19	29	34	20	40	44	57	10	41	48	0	.	87	43	59	29	17	49	56	40	0	.	35	31	67	28	52	55	152	41	37	40	53	25	39	23	35	35	29	48	38	27	61	42	21	35	24	40	25	44	46	48	47	89	35	25	46	49	44	55	72	47	39	38	37	39	30	27	15	60	54	34	74	41	46	76	33	28	27	49	55	35	11	89	38	42	0	.	41	30	0	.	47	56	29	52	0	.	43	51	61	19	102	51	42	39	34	31	0	.	165	38	150	.	54	72	15	54	51	86	23	75	0	.	29	40	0	.	31	48	30	74	29	58	52	30	12	88	4	90	0	.	0	.	20	.	24	48	81	36	53	28	42	60	22	46	21	39	41	53	19	32	30	27	59	52	27	36	0	.	39	5
	wood harvest	16	50	15	71	4	90	22	35	13	53	0	.	3	66	39	35	9	41	15	70	0	.	47	46	0	.	0	.	0	.	21	52	14	61	8	91	0	.	0	.	0	.	6	92	0	.	0	.	2	98	12	50	0	.	32	42	14	78	27	64	15	62	25	56	0	.	21	88	0	.	0	.	0	.	18	91	0	.	20	86	0	.	2	96	34	50	18	56	0	.	0	.	7	91	0	.	0	.	0	.	16	67	17	82	5	87	0	.	0	.	9	91	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	6	92	0	.	14	90	9	91	11	93	23	42	0	.	30	45	54	.	9	74	0	.	0	.	9	96	0	.	17	80	3	91	49	51	35	85	18	55	0	.	17	88	0	.	0	.	12	12
	other human activity	0	.	15	95	4	90	0	.	0	.	10	79	1	98	9	46	2	62	6	50	21	90	0	.	0	.	0	.	0	.	10	95	0	.	0	.	0	.	0	.	2	95	0	.	2	95	7	76	1	98	2	97	5	96	5	97	6	84	6	93	5	96	0	.	10	90	11	85	38	34	0	.	0	.	0	.	0	.	0	.	0	.	12	82	2	96	0	.	0	.	0	.	0	.	0	.	7	95	0	.	64	76	0	.	0	.	0	.	43	55	19	91	0	.	0	.	6	61	15	91	0	.	0	.	0	.	0	.	0	.	179	52	0	.	112	86	19	75	0	.	0	.	0	.	0	.	22	87	0	.	2	95	0	.	10	90	0	.	0	.	0	.	8	65	7	69	4	91	6	85	34	68	7	93	48	93	0	.	0	.	14	83	0	.	0	.	7	18
	weather	0	.	7	70	0	.	4	53	0	.	0	.	2	98	3	50	10	64	8	50	0	.	0	.	0	.	0	.	14	81	5	73	2	93	24	47	0	.	0	.	14	79	12	91	21	56	0	.	8	57	4	98	11	56	0	.	15	45	11	63	0	.	0	.	0	.	0	.	0	.	15	61	24	87	0	.	0	.	0	.	0	.	0	.	0	.	24	75	0	.	46	76	0	.	14	61	12	61	0	.	0	.	0	.	0	.	0	.	0	.	15	93	0	.	0	.	6	61	18	57	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	2	95	24	52	67	91	0	.	0	.	0	.	4	96	2	95	4	91	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	6	16
	lying living trees	0	.	0	.	0	.	0	.	6	95	0	.	3	96	0	.	0	.	4	98	0	.	0	.	0	.	0	.	16	84	3	96	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	3	68	0	.	0	.	3	97	3	96	5	95	2	96	0	.	10	90	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	5	96	0	.	0	.	0	.	0	.	0	.	0	.	9	92	0	.	0	.	0	.	0	.	50	.	0	.	0	.	0	.	5	87	6	94	0	.	0	.	0	.	0	.	0	.	0	.	0	.	13	86	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	4	96	5	87	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	1	24
	dead trees	4	97	26	65	9	87	27	33	6	95	52	30	34	28	26	32	26	29	27	33	0	.	0	.	41	44	0	.	88	42	78	50	43	47	17	91	0	.	26	69	19	55	32	58	68	32	38	53	56	29	49	38	28	38	26	45	165	38	27	49	13	50	9	91	0	.	51	34	42	89	50	66	54	30	8	91	40	43	36	78	31	86	20	45	28	31	22	57	10	90	0	.	25	63	13	71	118	82	73	39	12	62	17	82	0	.	0	.	49	57	42	53	0	.	149	51	60	51	79	39	18	77	79	67	0	.	6	83	150	.	89	9	25	43	11	91	59	12	100	.	43	43	0	.	20	54	0	.	112	48	19	41	69	23	39	56	272	.	0	.	0	.	39	36	80	59	35	22	50	50	3	91	25	44	14	60	23	49	17	81	12	88	10	91	0	.	39	9
	total	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.
41-60 %	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	.
	no visible damage	298	32	80	.	0	.	268	25	331	43	227	33	315	12	328	14	324	21	464	17	297	32	519	27	399	19	0	.	256	10	96	53	411	25	182	18	0	.	331	26	364	18	379	11	306	15	348	12	251	11	277	16	390	26	262	20	283	27	0	.	280	36	251	6	183	35	234	15	478	35	368	44	281	25	190	29	654	34	383	20	439	20	403	13	502	19	920	.	257	24	319	16	289	17	398	20	224	19	285	31	433	16	290	.	190	.	250	27	353	27	218	22	430	30	369	30	458	21	619	18	285	28	286	23	544	31	140	.	125	.	271	25	241	25	224	41	385	25	0	.	337	27	590	.	100	.	243	48	266	22	311	9	205	10	640	.	150	.	480	.	0	.	307	17	402	12	452	14	174	28	330	.	530	.	236	7	380	48	0	.	290	34	250	.	0	.	337	3
	fire	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	99	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	23	91	72	64	10	97	38	94	24	91	4	94	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	2	41
	rockfall	0	.	0	.	0	.	0	.	0	.	0	.	4	54	0	.	0	.	17	97	0	.	18	86	0	.	0	.	0	.	0	.	0	.	0	.	0	.	13	85	0	.	3	97	0	.	2	98	0	.	2	98	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	8	82	0	.	0	.	0	.	0	.	0	.	0	.	0	.	11	94	0	.	12	65	0	.	0	.	7	90	2	94	0	.	0	.	0	.	0	.	27	69	3	93	0	.	3	93	30	94	4	97	0	.	0	.	15	96	11	88	0	.	0	.	7	94	9	96	76	87	0	.	0	.	23	88	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	1	98	8	85	1	98	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	4	24
	various	0	.	0	.	0	.	0	.	16	84	0	.	10	33	0	.	14	62	3	97	16	83	7	87	0	.	0	.	0	.	0	.	42	50	0	.	0	.	4	97	13	77	8	42	9	68	7	40	9	30	9	64	26	65	7	69	18	64	0	.	0	.	11	67	0	.	0	.	29	60	0	.	2	96	0	.	0	.	40	47	7	92	25	34	17	47	0	.	0	.	8	91	6	94	0	.	11	64	9	68	6	83	0	.	0	.	15	93	3	93	13	51	113	50	31	67	14	43	0	.	20	94	72	75	0	.	0	.	0	.	7	94	4	94	0	.	0	.	0	.	6	72	0	.	0	.	0	.	17	80	0	.	5	89	50	.	0	.	0	.	0	.	8	48	5	52	6	49	8	92	0	.	0	.	10	90	0	.	0	.	10	71	0	.	0	.	11	13
	indeterminable	49	40	0	.	0	.	127	48	42	41	31	52	56	14	50	34	24	26	51	21	43	63	85	32	54	63	0	.	118	60	30	49	60	23	35	38	0	.	63	32	44	25	57	19	51	27	73	23	41	20	49	31	63	53	24	31	41	45	0	.	20	47	11	67	12	87	19	36	89	19	56	44	61	37	78	46	137	61	30	41	35	38	40	35	66	41	50	.	51	42	52	35	72	43	94	42	33	44	27	30	70	14	0	.	70	.	102	35	70	30	73	45	130	37	68	34	175	23	39	31	65	39	155	49	48	38	40	.	0	.	70	50	53	39	62	27	49	73	0	.	82	30	140	.	50	.	90	24	0	.	35	72	24	65	50	.	50	.	0	.	0	.	42	22	64	19	45	25	11	66	90	.	0	.	32	49	34	38	0	.	70	71	20	.	0	.	57	5
	wood harvest	13	75	0	.	0	.	0	.	0	.	0	.	6	55	20	31	19	40	3	97	0	.	0	.	0	.	0	.	36	69	8	74	30	59	10	88	0	.	8	65	15	89	5	79	7	88	3	59	2	75	22	62	3	92	37	45	25	71	0	.	0	.	0	.	12	87	18	91	29	60	0	.	3	93	0	.	3	94	0	.	0	.	3	96	0	.	0	.	7	71	21	76	31	94	0	.	42	34	0	.	16	83	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	21	88	0	.	0	.	0	.	0	.	0	.	0	.	0	.	13	50	0	.	0	.	0	.	12	85	0	.	0	.	0	.	0	.	20	.	0	.	0	.	6	99	5	98	32	92	0	.	0	.	54	55	0	.	0	.	0	.	0	.	0	.	8	14
	other human activity	0	.	0	.	0	.	0	.	0	.	15	63	12	63	3	66	0	.	19	97	0	.	0	.	0	.	0	.	0	.	0	.	15	69	0	.	0	.	2	96	2	97	4	73	6	48	8	63	0	.	12	30	0	.	8	95	13	76	0	.	37	42	0	.	12	88	8	92	0	.	12	87	8	66	0	.	10	94	4	96	12	62	25	60	0	.	0	.	0	.	0	.	16	51	0	.	23	71	0	.	16	83	0	.	0	.	0	.	7	94	7	93	0	.	0	.	0	.	0	.	0	.	7	96	41	90	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	4	69	6	73	0	.	8	92	0	.	0	.	0	.	4	90	0	.	0	.	0	.	0	.	6	17
	weather	0	.	0	.	0	.	35	81	0	.	0	.	8	39	14	54	3	65	11	48	0	.	0	.	8	91	0	.	0	.	0	.	4	95	45	44	0	.	0	.	13	59	1	98	4	68	5	55	5	59	8	60	11	92	8	70	0	.	0	.	0	.	0	.	0	.	0	.	21	82	0	.	10	69	6	87	3	94	13	82	6	94	0	.	2	94	0	.	0	.	0	.	3	94	15	94	12	61	12	95	0	.	0	.	0	.	27	69	60	33	9	64	14	93	11	94	22	51	6	94	11	64	13	56	11	88	0	.	0	.	0	.	11	62	0	.	17	82	0	.	5	95	0	.	0	.	25	72	0	.	0	.	0	.	0	.	0	.	0	.	0	.	4	70	11	46	29	38	0	.	0	.	0	.	10	90	10	89	0	.	0	.	50	.	0	.	8	11
	lying living trees	3	94	50	.	0	.	0	.	0	.	0	.	1	99	3	96	0	.	0	.	16	83	0	.	0	.	0	.	0	.	16	83	0	.	0	.	0	.	0	.	0	.	1	97	4	98	0	.	1	99	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	22	91	0	.	18	78	0	.	9	64	0	.	4	95	0	.	0	.	0	.	0	.	0	.	7	94	0	.	0	.	0	.	0	.	0	.	13	93	0	.	0	.	28	93	30	74	7	97	0	.	0	.	0	.	0	.	0	.	0	.	0	.	6	94	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	3	68	1	99	17	89	0	.	0	.	0	.	20	89	0	.	0	.	25	71	0	.	0	.	3	26
	dead trees	46	42	0	.	0	.	69	55	103	55	102	36	77	18	48	37	17	37	42	26	73	50	59	45	37	58	0	.	136	34	65	64	41	49	145	43	0	.	50	48	29	36	22	29	73	25	59	26	25	30	52	24	112	52	58	43	54	38	0	.	0	.	0	.	0	.	21	59	51	82	23	54	67	45	55	64	69	47	52	40	57	72	62	38	33	54	0	.	43	42	35	58	43	46	66	41	49	43	35	45	0	.	0	.	0	.	75	36	40	38	26	71	89	60	61	50	157	21	65	61	18	59	74	40	21	51	0	.	86	.	29	49	46	49	33	50	85	51	0	.	91	24	50	.	0	.	74	72	17	80	50	0	27	44	170	.	50	.	70	.	0	.	46	31	74	24	98	34	47	40	0	.	50	.	130	39	44	45	0	.	0	.	40	.	0	.	57	6
	total	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.
61-80 %	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	.
	no visible damage	175	22	0	.	0	.	0	.	390	.	290	.	301	12	314	16	303	18	423	22	0	.	220	48	338	21	0	.	0	.	0	.	282	39	820	.	0	.	320	19	253	12	205	14	371	30	376	12	329	11	449	12	223	24	130	.	365	20	220	.	270	.	0	.	150	.	472	34	667	50	486	41	293	39	180	.	400	29	374	32	274	26	251	31	0	.	298	31	330	31	0	.	353	52	273	24	50	.	378	26	0	.	0	.	0	.	302	46	338	28	375	49	351	31	363	28	424	21	410	18	337	15	395	29	352	32	520	.	413	16	307	22	397	25	476	39	370	.	0	.	100	.	0	.	768	37	0	.	280	.	0	.	0	.	0	.	0	.	0	.	0	.	293	11	376	28	355	13	0	.	841	34	0	.	223	37	90	.	0	.	0	.	0	.	0	.	342	4
	fire	0	.	0	.	0	.	0	.	0	.	0	.	0	99	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	19	99	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	2	94	0	.	0	.	0	.	6	95	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	2	98	0	.	0	.	0	.	12	87	0	.	0	.	0	.	0	.	0	.	2	83
	rockfall	0	.	0	.	0	.	0	.	0	.	0	.	26	36	7	51	53	81	149	29	0	.	0	.	176	79	0	.	0	.	0	.	88	88	0	.	0	.	32	39	7	72	24	87	7	65	27	30	16	61	9	95	0	.	0	.	1	97	90	.	0	.	0	.	200	.	129	60	24	88	0	.	135	43	0	.	6	82	14	51	103	85	70	80	0	.	14	38	7	81	0	.	0	.	71	40	0	.	4	89	0	.	0	.	0	.	7	79	11	94	33	75	0	.	74	46	75	57	8	96	22	59	24	46	125	41	0	.	28	48	6	68	72	55	14	64	0	.	0	.	0	.	0	.	0	.	0	.	40	.	0	.	0	.	0	.	0	.	0	.	0	.	23	39	15	59	26	72	0	.	25	70	0	.	25	87	0	.	0	.	0	.	0	.	0	.	31	11
	various	0	.	0	.	0	.	0	.	0	.	0	.	5	45	1	97	0	.	20	51	0	.	0	.	23	40	0	.	0	.	0	.	24	69	0	.	0	.	3	97	12	38	17	42	11	68	11	44	7	73	7	95	0	.	0	.	3	65	0	.	0	.	0	.	0	.	0	.	24	53	0	.	5	96	0	.	0	.	19	57	21	54	30	86	0	.	0	.	23	51	0	.	0	.	12	63	0	.	12	85	0	.	0	.	0	.	0	.	37	93	79	67	6	93	9	67	0	.	4	96	15	55	6	68	2	95	0	.	2	95	10	56	5	86	10	89	0	.	0	.	0	.	0	.	0	.	0	.	20	.	0	.	0	.	0	.	0	.	0	.	0	.	3	99	19	42	8	46	0	.	0	.	0	.	5	88	0	.	0	.	0	.	0	.	0	.	9	13
	indeterminable	30	24	0	.	0	.	0	.	20	.	120	.	44	16	27	33	62	68	43	34	0	.	20	71	83	34	0	.	0	.	0	.	42	50	50	.	0	.	56	23	68	17	67	24	31	23	64	17	77	14	63	37	20	47	70	.	52	43	0	.	0	.	0	.	0	.	0	.	76	21	86	80	48	33	300	.	130	21	47	30	103	41	63	66	0	.	136	21	157	24	0	.	12	68	53	46	50	.	97	32	0	.	0	.	0	.	23	53	30	51	212	67	117	78	62	23	151	41	60	48	108	32	115	40	52	21	340	.	52	34	44	43	57	50	79	52	160	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	45	19	74	24	67	18	0	.	85	71	0	.	41	53	50	.	0	.	0	.	0	.	0	.	63	6
	wood harvest	0	.	0	.	0	.	0	.	0	.	0	.	5	69	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	11	67	6	58	0	.	11	96	2	46	11	63	0	.	0	.	20	.	22	82	0	.	0	.	0	.	0	.	0	.	9	88	0	.	0	.	0	.	39	53	14	68	0	.	0	.	0	.	13	84	17	81	0	.	19	74	0	.	20	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	15	57	6	94	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	2	69	4	76	8	79	0	.	0	.	0	.	31	86	0	.	0	.	0	.	0	.	0	.	5	20
	other human activity	0	.	0	.	0	.	0	.	0	.	0	.	4	72	4	68	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	42	92	0	.	0	.	9	97	2	98	0	.	4	96	4	43	11	79	2	93	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	12	88	0	.	0	.	0	.	0	.	2	95	15	89	49	80	0	.	0	.	0	.	0	.	0	.	0	.	0	.	18	89	0	.	0	.	0	.	0	.	0	.	0	.	0	.	15	94	2	94	0	.	4	95	0	.	3	93	270	.	8	66	0	.	0	.	4	91	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	9	66	1	98	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	5	24
	weather	0	.	0	.	0	.	0	.	0	.	0	.	15	27	19	41	0	.	7	76	0	.	0	.	0	.	0	.	0	.	0	.	23	76	0	.	0	.	38	45	5	67	7	70	3	96	19	33	4	58	4	95	52	80	50	.	18	55	0	.	0	.	0	.	0	.	0	.	0	.	0	.	13	52	0	.	0	.	5	95	17	89	0	.	0	.	0	.	0	.	0	.	39	68	0	.	0	.	48	85	0	.	0	.	0	.	39	64	13	79	80	75	48	59	0	.	13	93	18	52	0	.	7	71	6	95	0	.	8	65	21	50	0	.	0	.	0	.	0	.	0	.	0	.	23	75	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	26	24	16	51	11	44	0	.	0	.	0	.	5	88	0	.	0	.	0	.	0	.	0	.	14	11
	lying living trees	0	.	0	.	0	.	0	.	0	.	0	.	3	66	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	10	67	21	98	2	95	8	65	12	71	5	99	0	.	24	80	0	.	8	66	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	5	97	9	92	0	.	0	.	0	.	0	.	0	.	26	68	0	.	0	.	0	.	0	.	0	.	0	.	0	.	2	95	0	.	0	.	6	94	3	93	6	96	8	65	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	9	46	19	56	2	98	0	.	0	.	0	.	12	87	0	.	0	.	0	.	0	.	0	.	6	24
	dead trees	25	71	0	.	0	.	0	.	70	.	120	.	89	19	57	35	86	42	24	51	0	.	0	.	98	46	0	.	0	.	0	.	175	46	200	.	0	.	85	29	59	26	88	39	54	60	93	19	44	25	61	27	129	38	50	.	131	23	0	.	50	.	0	.	0	.	109	71	62	32	151	25	41	38	0	.	36	37	48	33	90	32	92	18	0	.	37	78	166	41	0	.	106	29	49	49	0	.	108	50	0	.	0	.	0	.	65	83	50	35	24	75	58	45	108	22	109	36	30	53	44	47	136	27	20	57	20	.	101	33	73	32	39	53	109	60	70	.	0	.	20	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	71	21	41	24	87	33	0	.	120	18	0	.	72	37	0	.	0	.	0	.	0	.	0	.	73	6
	total	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.
81-100 %	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	.
	no visible damage	0	.	70	.	0	.	0	.	212	9	446	15	266	22	142	23	0	.	611	5	0	.	0	.	42	.	0	.	0	.	1364	.	162	57	0	.	0	.	171	28	237	16	186	27	296	24	309	21	364	32	390	.	0	.	0	.	490	.	0	.	0	.	0	.	0	.	90	.	478	12	370	.	264	28	340	.	300	22	201	38	0	.	460	.	0	.	120	.	220	.	218	42	250	.	243	42	224	76	307	10	0	.	0	.	0	.	536	44	259	27	374	11	410	34	231	77	384	21	187	39	510	38	401	20	492	38	222	23	801	15	338	66	208	19	315	53	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	419	27	301	25	282	18	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	317	6
	fire	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	50	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	10	90	0	.	0	.	0	.	58	94	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	6	94	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	3	77
	rockfall	0	.	0	.	0	.	0	.	10	71	25	70	67	43	0	.	0	.	380	68	0	.	0	.	392	.	0	.	0	.	0	.	46	87	0	.	0	.	201	35	17	39	64	47	0	.	36	47	41	82	0	.	0	.	0	.	230	.	0	.	0	.	0	.	0	.	20	.	146	44	0	.	279	70	0	.	77	25	117	35	0	.	0	.	0	.	210	.	380	.	275	6	180	.	0	.	11	66	0	.	0	.	0	.	0	.	4	89	22	53	0	.	17	57	125	35	137	43	12	49	22	93	49	47	44	86	86	5	0	.	207	71	69	53	180	8	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	39	29	13	52	48	37	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	64	12
	various	0	.	0	.	0	.	0	.	25	71	109	59	6	77	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	10	69	5	88	25	62	4	90	0	.	17	58	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	25	70	0	.	5	85	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	10	90	9	91	10	67	0	.	19	94	0	.	0	.	0	.	12	71	22	80	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	2	94	3	73	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	6	25
	indeterminable	0	.	20	.	0	.	0	.	102	5	10	70	63	26	74	15	0	.	95	4	0	.	0	.	100	.	0	.	0	.	303	.	11	91	0	.	0	.	37	35	61	28	99	29	78	40	96	31	78	30	70	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	40	.	25	87	50	.	81	35	170	.	117	50	25	46	0	.	120	.	0	.	0	.	170	.	25	72	170	.	32	66	61	12	17	84	0	.	0	.	0	.	42	37	79	50	76	44	100	82	14	63	126	30	65	34	70	69	146	41	145	42	39	71	126	20	80	70	50	49	35	30	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	25	38	97	30	29	33	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	69	9
	wood harvest	0	.	0	.	0	.	0	.	0	.	0	.	2	97	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	9	88	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	20	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	17	80	0	.	0	.	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	52
	other human activity	0	.	0	.	0	.	0	.	0	.	0	.	0	.	20	1	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	17	75	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	17	82	7	93	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	2	94	39	87	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	25	70	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	1	97	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	3	43
	weather	0	.	50	.	0	.	0	.	0	.	0	.	13	68	0	.	0	.	25	70	0	.	0	.	0	.	0	.	0	.	0	.	60	44	0	.	0	.	6	60	4	92	0	.	30	89	18	63	8	91	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	13	87	150	.	0	.	0	.	17	82	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	47	49	104	61	40	84	0	.	0	.	0	.	20	54	19	64	0	.	24	61	11	87	15	92	0	.	13	94	12	94	0	.	0	.	0	.	0	.	34	80	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	19	59	2	94	28	27	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	15	15
	lying living trees	0	.	50	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	7	92	0	.	0	.	10	89	2	96	8	91	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	20	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	8	93	0	.	0	.	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	55	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	2	34
	dead trees	0	.	90	.	0	.	0	.	36	27	86	70	138	36	19	76	0	.	46	70	0	.	0	.	50	.	0	.	0	.	363	.	153	38	0	.	0	.	83	43	140	26	27	58	69	46	94	28	69	42	0	.	0	.	0	.	170	.	0	.	0	.	0	.	0	.	20	.	18	58	40	.	50	0	100	.	80	72	59	53	0	.	0	.	0	.	100	.	150	.	198	54	100	.	59	58	154	41	0	.	0	.	0	.	0	.	19	56	53	35	27	57	79	58	20	90	208	20	42	84	74	76	141	39	90	43	79	71	112	57	286	54	31	85	75	24	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	107	40	105	33	121	19	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	91	9
	total	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.
>100%	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	.
	no visible damage	0	.	0	.	0	.	0	.	370	.	0	.	253	23	70	.	0	.	478	.	0	.	0	.	0	.	0	.	0	.	0	.	303	60	0	.	0	.	40	.	220	55	0	.	270	15	258	26	280	56	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	445	.	170	35	0	.	390	.	0	.	0	.	829	28	206	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	25	.	0	.	0	.	0	.	0	.	220	.	290	37	360	19	213	46	0	.	0	.	332	33	0	.	51	.	603	.	0	.	180	46	0	.	0	.	474	71	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	190	29	200	.	259	23	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	272	9
	fire	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	rockfall	0	.	0	.	0	.	0	.	110	.	0	.	63	41	510	.	0	.	76	.	0	.	0	.	0	.	0	.	0	.	0	.	28	82	0	.	0	.	130	.	150	47	0	.	28	54	104	42	25	71	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	110	40	0	.	70	.	0	.	0	.	185	64	1208	.	0	.	0	.	0	.	0	.	0	.	0	.	100	.	281	.	0	.	0	.	0	.	0	.	150	.	35	40	31	81	30	76	0	.	0	.	90	54	0	.	146	.	0	.	0	.	173	68	0	.	0	.	101	65	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	86	40	0	.	153	42	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	105	18
	various	0	.	0	.	0	.	0	.	20	.	0	.	7	97	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	29	60	0	.	0	.	0	.	45	71	0	.	25	87	2	95	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	59	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	100	.	0	.	0	.	0	.	0	.	0	.	48	59	0	.	0	.	0	.	0	.	12	68	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	10	89	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	11	32
	indeterminable	0	.	0	.	0	.	0	.	0	.	0	.	51	34	50	.	0	.	261	.	0	.	0	.	0	.	0	.	0	.	0	.	72	60	0	.	0	.	110	.	170	21	0	.	42	55	40	29	25	71	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	93	11	0	.	20	.	0	.	0	.	55	77	236	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	82	.	0	.	0	.	0	.	0	.	0	.	170	59	24	49	141	38	0	.	0	.	59	35	0	.	146	.	25	.	0	.	198	18	0	.	0	.	260	22	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	48	38	50	.	49	40	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	75	13
	wood harvest	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	other human activity	0	.	0	.	0	.	0	.	0	.	0	.	6	94	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	118	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	22	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	3	65
	weather	0	.	0	.	0	.	0	.	0	.	0	.	25	42	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	9	82	0	.	0	.	0	.	0	.	0	.	11	90	10	62	25	71	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	76	39	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	50	.	0	.	17	81	9	92	0	.	0	.	14	93	0	.	101	.	0	.	0	.	12	68	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	8	55	0	.	6	92	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	14	23
	lying living trees	0	.	0	.	0	.	0	.	0	.	0	.	2	96	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	2	94	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	100	.	0	.	0	.	0	.	59	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	17	81	0	.	0	.	0	.	0	.	0	.	101	.	54	.	0	.	48	73	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	40	42	0	.	21	93	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	10	31
	dead trees	0	.	0	.	0	.	0	.	150	.	0	.	78	36	20	.	0	.	185	.	0	.	0	.	0	.	0	.	0	.	0	.	113	82	0	.	0	.	140	.	110	26	0	.	56	52	45	48	30	71	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	158	.	123	29	0	.	320	.	0	.	0	.	114	25	118	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	25	.	0	.	0	.	0	.	0	.	0	.	0	.	105	54	131	53	0	.	0	.	56	41	0	.	51	.	54	.	0	.	222	0	0	.	0	.	129	11	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	115	49	0	.	92	21	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	86	12
	total	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.
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	.
	no visible damage	245	16	251	19	373	17	236	12	366	15	433	13	306	7	299	7	314	7	410	7	204	21	313	18	335	12	190	.	309	20	404	15	325	15	331	15	334	25	293	14	285	9	300	10	319	11	338	8	325	7	321	7	365	14	346	10	419	9	351	17	383	11	336	12	294	16	317	13	481	22	425	19	344	17	313	17	425	20	338	16	358	13	333	10	386	10	350	14	270	15	223	16	335	13	334	13	290	15	300	15	403	16	394	15	350	15	318	27	329	14	314	11	355	17	325	19	453	12	406	13	367	16	348	14	451	19	367	18	414	15	321	14	299	19	473	24	429	22	354	30	340	15	301	31	326	30	341	11	404	18	405	17	289	14	503	27	319	24	327	28	376	28	319	9	375	10	355	8	273	18	352	20	268	16	292	17	287	12	287	17	294	17	333	18	0	.	337	1
	fire	0	.	0	.	0	.	0	.	0	.	0	.	0	100	0	.	0	.	0	.	0	.	0	.	2	98	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	8	100	0	100	0	.	1	99	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	2	98	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	6	98	26	62	4	99	8	99	5	98	17	81	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	100	0	99	1	99	0	.	0	.	0	.	2	98	0	.	0	.	0	.	0	.	0	.	1	37
	rockfall	0	.	0	.	0	.	0	.	8	83	2	98	22	24	6	80	1	100	41	33	0	.	5	97	54	66	0	.	0	.	0	.	20	72	0	.	0	.	55	31	9	52	13	48	3	49	24	24	7	49	1	74	0	.	0	.	5	92	7	96	0	.	0	.	14	97	11	84	59	39	0	.	70	41	0	.	12	53	37	38	84	71	6	99	3	99	11	82	24	72	29	67	10	88	22	42	13	86	1	98	0	.	0	.	0	.	21	51	16	35	7	68	10	52	55	33	40	39	21	51	15	52	29	32	68	40	22	61	39	54	26	79	26	43	52	42	0	.	0	.	10	90	0	.	0	.	0	.	2	97	0	.	0	.	0	.	0	.	0	.	0	.	17	27	10	42	31	31	0	.	3	97	0	.	3	98	0	.	0	.	0	.	0	.	0	.	15	8
	various	1	69	0	.	5	78	3	58	14	43	12	64	7	22	2	50	7	44	14	43	8	55	9	50	7	50	0	.	11	79	4	57	18	37	2	55	0	.	5	46	12	32	11	28	14	36	9	31	10	27	8	33	15	46	6	38	11	39	5	73	9	71	2	95	14	54	7	49	16	36	0	.	10	50	1	98	0	.	24	37	14	36	15	31	6	43	6	55	3	74	5	67	7	53	7	43	4	69	12	41	8	43	1	98	3	75	11	67	10	93	12	57	32	56	15	49	7	42	13	47	13	46	32	61	1	98	0	.	3	66	8	44	11	42	3	97	7	66	0	.	8	63	3	91	0	.	11	44	4	74	6	57	7	56	21	58	0	.	0	.	10	68	4	43	9	30	5	31	14	62	3	97	2	67	9	46	1	99	8	50	6	43	4	72	0	.	8	7
	indeterminable	37	21	28	26	29	26	21	38	46	24	43	23	50	9	31	14	28	12	41	14	33	35	53	21	48	30	0	.	88	26	51	26	38	20	41	24	37	65	54	16	60	12	65	15	62	20	64	12	60	11	46	15	37	23	33	24	41	21	52	35	32	43	27	31	25	37	24	24	59	21	40	33	49	21	66	27	97	30	36	19	67	26	36	21	38	30	50	25	75	22	35	27	61	30	52	27	45	21	43	28	40	31	29	33	26	29	56	32	68	25	72	29	122	30	52	19	137	17	62	21	82	25	130	25	71	26	145	29	81	23	55	29	45	25	84	29	49	35	9	44	55	25	48	37	19	46	23	30	21	40	46	25	31	28	25	35	13	56	0	.	16	77	40	12	72	12	48	13	20	42	37	32	27	29	33	24	25	21	36	32	55	31	22	25	0	.	50	3
	wood harvest	13	33	5	76	7	69	21	29	6	59	0	.	4	39	22	27	12	19	9	51	0	.	21	42	9	66	0	.	15	56	14	43	11	49	14	35	0	.	7	50	6	66	4	53	6	66	3	40	4	52	16	33	10	54	26	26	17	45	18	67	13	46	17	41	5	72	12	46	6	67	0	.	1	98	6	83	8	65	6	59	0	.	6	53	19	36	12	44	8	48	10	63	16	74	0	.	16	40	0	.	13	48	8	53	13	58	0	.	0	.	2	98	0	.	0	.	0	.	0	.	0	.	0	.	6	97	0	.	10	59	2	98	2	98	0	.	8	69	6	93	8	42	7	94	6	96	4	59	6	71	14	46	12	72	14	55	10	53	62	70	0	.	1	70	5	63	4	62	23	65	8	81	26	45	27	39	11	44	4	74	6	77	3	97	0	.	8	7
	other human activity	1	99	5	98	1	97	0	.	0	.	9	52	6	46	7	33	2	51	7	62	9	96	0	.	0	.	20	.	0	.	5	98	10	67	1	98	8	90	4	88	2	50	3	61	4	41	6	35	4	64	5	28	2	79	5	47	5	58	5	73	10	46	0	.	11	52	12	56	10	52	3	76	2	71	7	71	5	68	3	58	19	42	18	44	2	75	0	.	1	98	0	.	7	58	0	.	11	60	4	98	27	75	0	.	2	98	1	98	8	53	17	56	0	.	4	98	2	56	2	99	2	98	3	79	13	88	34	94	5	67	20	74	0	.	28	93	6	67	0	.	4	68	0	.	0	.	6	71	3	98	2	67	0	.	5	95	0	.	0	.	0	.	2	50	7	41	1	57	5	72	15	69	5	67	14	85	1	99	0	.	7	60	3	97	0	.	5	9
	weather	0	.	4	59	0	.	6	50	0	.	0	.	11	19	8	28	8	30	8	31	0	.	9	83	3	98	0	.	8	65	5	63	12	43	11	42	4	90	18	45	8	40	3	56	11	37	12	26	6	28	5	38	11	46	5	55	12	34	7	66	0	.	0	.	0	.	0	.	18	49	14	55	12	44	1	98	3	76	5	67	6	70	0	.	1	99	10	79	0	.	5	98	5	79	14	43	17	46	20	61	3	98	0	.	2	98	26	37	23	32	16	51	25	40	6	71	15	38	11	37	6	63	13	40	5	67	0	.	6	55	9	56	9	57	0	.	4	96	15	60	2	98	0	.	9	65	2	99	0	.	1	97	10	45	36	83	0	.	9	88	3	94	15	21	10	33	19	22	4	97	1	97	0	.	2	75	2	98	0	.	0	.	3	97	0	.	8	6
	lying living trees	1	99	3	69	0	.	1	99	3	97	0	.	2	47	1	99	0	.	1	99	4	96	0	.	0	.	0	.	4	96	3	68	0	.	0	.	0	.	6	58	7	99	2	62	5	45	6	68	4	50	0	.	2	99	1	99	3	56	3	97	1	98	0	.	3	97	0	.	0	.	7	72	3	99	3	97	0	.	4	56	5	69	3	69	0	.	0	.	0	.	0	.	4	75	2	99	4	97	0	.	5	97	0	.	0	.	8	71	1	99	2	98	9	82	13	64	5	66	2	99	4	68	3	98	3	98	0	.	6	97	0	.	5	67	0	.	0	.	7	93	0	.	0	.	0	.	0	.	0	.	2	98	1	97	0	.	0	.	0	.	0	.	7	33	5	53	10	52	0	.	0	.	0	.	5	72	0	.	0	.	7	66	0	.	0	.	3	13
	dead trees	18	33	21	35	3	96	26	24	41	40	71	22	80	12	33	18	19	17	31	17	26	54	29	45	49	28	0	.	82	42	67	35	73	26	48	29	58	35	70	21	48	17	45	24	64	19	73	13	40	15	45	16	46	31	31	24	122	23	31	34	16	46	12	51	4	96	38	29	53	27	70	34	60	23	22	38	51	28	52	21	56	33	40	28	22	28	21	39	56	31	33	56	47	25	41	27	79	51	53	34	15	58	15	68	11	54	45	35	44	21	38	32	83	29	88	23	134	15	51	26	43	40	107	20	38	34	50	54	119	21	78	32	36	31	66	35	34	42	78	48	55	24	46	77	11	54	20	35	60	41	24	25	49	32	37	45	47	49	18	85	16	47	64	14	68	17	92	16	38	32	33	36	22	29	40	31	17	38	29	29	8	67	22	32	0	.	51	3
	total	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.	.

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. 2289151. Birmensdorf, Swiss Federal Research Institute WSL

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