Selection from the list of topics

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

1. What do the numbers stand for?

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

Example 1: Estimated value and standard error

NFI5

volume of deadwood (stemwood)
ownership (2 categories)

regional demarcation: production region

unit: m³/ha

evaluation area: accessible forest without shrub forest

grid: 1.4 km grid, subgrids 1-5

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

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

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2. What is the purpose of the standard error?

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

The statistical certainty is:

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

Example 2: Calculating confidence intervals

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

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

Procedure

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

Answer

			Step 1	Step 2

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

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

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

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

Data: see example 2

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

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

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3. When are two results statistically different?*

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

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

Example 4: Interpretation of two results from the same inventory

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

	case 2						case 1

case 1

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

Procedure

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

Answer

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

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

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

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

Case 2

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

Procedure

See case 1.

Answer

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

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

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

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

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

Example 5: Interpretation of two results from different inventories

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

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

Procedure

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

Answer

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

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

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

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

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

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

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

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

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

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

Procedure

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

Answer

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

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

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

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

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

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

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

Procedure

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

Answer

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

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

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

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

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

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

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

Example 8: Standard error and combination of variable expressions

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

The standard error increases as the level of detail increases.

Large standard errors are to be expected if:

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

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

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

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5. Two types of changes?

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

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

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

The results are:

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

Example 9: : Additivity/non-additivity of changes

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

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

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

Example 10: Average number of years per domain

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

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

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

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

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

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

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

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

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

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

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NFI2
growing stock (stemwood)
altitudinal vegetation belts (NaiS; 6 classes) · diameter at breast height (10 classes)
regional demarcation: forest district (2024)
unit: 1000 m³
evaluation area: accessible forest without shrub forest
grid: 1.4-km grid
state 1993/95
		forest district (2024)
		AG01		AG02		AG03		AG04		AI01		AR01		BE01		BE02		BE03		BE04		BSBL01		BSBL02		BSBL03		BSBL04		FR01		FR02		FR03		FR04		GE01		GL01		GR01		GR02		GR03		GR04		GR05		JU01		LU01		LU02		LU03		NE01		NE02		NE03		NE04		NE06		NW01		OW01		OW02		SG01		SG02		SG03		SG04		SG05		SH01		SO01		SO02		SO03		SO04		SZ01		SZ02		SZ03		TG01		TG02		TG03		TI01		TI02		TI03		TI04		TI05		TI06		TI07		TI08		TI09		UR01		UR02		UR03		VD02		VD03		VD04		VD05		VD06		VD07		VD08		VD09		VD11		VD12		VD14		VD15		VD16		VD18		VD20		VD22		VS01		VS02		VS03		ZG01		ZH01		ZH02		ZH03		ZH04		ZH05		ZH06		ZH07		lakes		Switzerland
altitudinal vegetation belts (NaiS; 6 classes)	diameter at breast height (10 classes)	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	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	12-20 cm	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	5	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	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	.
	21-30 cm	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	5	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	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	.
	31-40 cm	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	10	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	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	.
	41-50 cm	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	51-60 cm	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	61-70 cm	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	71-80 cm	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	81-90 cm	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	91-100 cm	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	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 cm	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	total	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	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	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	20	.
upper subalpine	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	.
	12-20 cm	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	1	100	3	.	3	.	14	35	276	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	.	8	53	11	67	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	1	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	78	40	36	31	4	71	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	435	15
	21-30 cm	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	34	62	11	.	3	.	60	36	467	18	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	5	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	17	60	14	73	0	.	0	.	0	.	11	100	0	.	0	.	0	.	0	.	27	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	179	27	137	42	30	71	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	996	12
	31-40 cm	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	24	62	9	.	0	.	115	37	611	20	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	8	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	17	74	21	81	0	.	0	.	0	.	8	100	0	.	0	.	0	.	0	.	-7	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	266	26	78	53	5	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	1155	13
	41-50 cm	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	17	77	0	.	0	.	108	35	503	18	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	15	74	0	.	0	.	0	.	0	.	21	100	0	.	0	.	0	.	0	.	7	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	334	21	63	40	13	75	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	1081	12
	51-60 cm	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	20	100	15	.	0	.	96	44	415	23	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	15	71	7	100	0	.	0	.	0	.	9	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	141	30	75	40	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	793	15
	61-70 cm	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	12	100	0	.	0	.	70	52	131	36	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	22	71	10	100	0	.	0	.	0	.	13	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	149	38	39	51	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	446	20
	71-80 cm	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	64	51	125	41	0	.	0	.	0	.	0	.	0	.	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	100	0	.	0	.	0	.	0	.	17	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	74	53	9	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	305	25
	81-90 cm	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	60	58	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	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	100	18	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	91	46
	91-100 cm	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	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	59	58	0	0	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	71	51
	>100 cm	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	18	100	45	73	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	20	100	17	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	100	46
	total	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	108	62	38	.	6	.	545	30	2644	14	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	14	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	112	46	64	61	0	.	0	.	0	.	78	72	0	.	0	.	0	.	0	.	28	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	1311	19	472	31	52	63	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	5473	9
subalpine	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	.
	12-20 cm	0	.	0	.	0	.	0	.	0	.	0	.	169	20	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	3	.	0	.	0	.	12	114	86	31	53	47	111	23	184	22	289	24	0	.	0	.	0	.	5	137	0	.	0	.	0	.	0	.	0	.	29	78	25	74	39	57	0	.	10	100	13	78	0	.	9	.	0	.	0	.	0	.	0	.	0	.	2	100	0	.	0	.	0	.	0	.	0	.	3	82	38	34	31	55	8	83	0	.	0	.	30	62	4	72	8	.	0	.	9	60	10	100	14	60	2	80	10	70	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	5	.	0	.	0	.	0	.	0	.	154	21	172	26	132	31	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	1669	8
	21-30 cm	0	.	0	.	0	.	0	.	0	.	0	.	602	18	4	77	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	31	115	287	28	155	34	330	29	635	23	673	19	0	.	0	.	0	.	11	84	0	.	0	.	0	.	0	.	0	.	36	64	39	86	112	53	0	.	8	100	86	45	0	.	-2	.	0	.	0	.	0	.	0	.	0	.	11	74	0	.	0	.	0	.	0	.	0	.	15	74	89	41	50	54	6	100	0	.	0	.	47	45	16	82	20	.	3	.	35	73	3	100	12	72	29	74	38	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	5	.	0	.	0	.	0	.	0	.	463	25	491	23	398	33	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	4739	7
	31-40 cm	0	.	0	.	0	.	0	.	0	.	0	.	858	21	45	71	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	117	67	347	30	198	32	573	23	708	19	967	18	0	.	0	.	0	.	18	100	0	.	0	.	0	.	0	.	0	.	37	58	45	56	94	48	0	.	13	74	112	50	0	.	1	.	0	.	0	.	0	.	0	.	0	.	53	86	0	.	0	.	0	.	0	.	0	.	65	50	138	35	81	52	0	.	0	.	0	.	65	40	29	73	0	.	0	.	39	72	9	100	43	100	50	52	11	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	16	.	0	.	0	.	0	.	0	.	683	21	575	22	555	26	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	6545	6
	41-50 cm	0	.	0	.	0	.	0	.	0	.	0	.	776	23	16	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	104	56	492	26	243	58	686	21	1015	19	1345	15	0	.	0	.	0	.	4	100	0	.	0	.	0	.	0	.	0	.	3	199	49	72	46	54	0	.	8	100	100	82	0	.	0	.	0	.	0	.	0	.	0	.	0	.	18	74	0	.	0	.	0	.	0	.	0	.	67	48	195	36	67	52	5	100	0	.	0	.	81	53	33	61	0	.	9	.	50	91	12	100	27	71	49	53	96	56	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	23	.	0	.	0	.	0	.	0	.	701	21	708	22	497	22	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	7525	6
	51-60 cm	0	.	0	.	0	.	0	.	0	.	0	.	509	20	20	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	75	66	381	30	69	46	454	24	565	19	946	19	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	39	100	15	72	36	75	0	.	12	100	37	50	0	.	-7	.	0	.	0	.	0	.	0	.	0	.	35	78	0	.	0	.	0	.	0	.	0	.	112	48	157	39	44	62	0	.	0	.	0	.	93	43	10	100	0	.	2	.	41	78	11	100	85	72	-6	100	41	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	15	.	0	.	0	.	0	.	0	.	568	23	489	31	359	28	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	5210	7
	61-70 cm	0	.	0	.	0	.	0	.	0	.	0	.	308	29	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	34	71	220	36	87	53	208	34	348	32	212	31	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	19	71	13	100	25	76	0	.	26	72	36	84	0	.	0	.	0	.	0	.	0	.	0	.	0	.	30	100	0	.	0	.	0	.	0	.	0	.	59	51	59	51	16	100	0	.	0	.	0	.	24	72	17	100	0	.	16	.	12	100	0	.	0	.	37	59	96	63	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	407	32	134	34	123	45	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	2565	10
	71-80 cm	0	.	0	.	0	.	0	.	0	.	0	.	92	55	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	39	71	122	47	0	.	120	50	60	50	87	47	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	17	100	30	100	0	.	0	.	18	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	34	71	0	.	0	.	0	.	0	.	0	.	49	59	45	59	43	100	0	.	0	.	0	.	37	72	0	.	0	.	19	.	0	.	0	.	57	71	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	303	30	19	100	28	71	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	1218	14
	81-90 cm	0	.	0	.	0	.	0	.	0	.	0	.	57	59	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	17	100	27	100	28	71	53	58	0	.	46	71	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	13	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	15	100	39	100	19	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	18	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	109	45	35	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	479	22
	91-100 cm	0	.	0	.	0	.	0	.	0	.	0	.	18	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	20	100	0	.	0	.	33	100	0	.	15	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	27	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	26	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	26	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	165	39
	>100 cm	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	54	100	0	.	0	.	33	100	0	.	19	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	33	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	140	53
	total	0	.	0	.	0	.	0	.	0	.	0	.	3388	17	85	76	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	3	.	0	.	0	.	503	48	1963	21	834	27	2602	18	3514	15	4600	13	0	.	0	.	0	.	39	97	0	.	0	.	0	.	0	.	0	.	164	58	203	52	383	41	0	.	77	71	443	40	0	.	1	.	0	.	0	.	0	.	0	.	0	.	182	62	0	.	0	.	0	.	0	.	0	.	412	35	761	27	352	44	19	73	0	.	0	.	378	35	108	52	29	.	48	.	186	66	44	79	238	66	162	48	309	61	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	65	.	0	.	0	.	0	.	0	.	3446	16	2623	19	2092	20	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	30256	5
high-montane	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	.
	12-20 cm	0	.	0	.	0	.	0	.	2	.	0	.	457	22	23	65	0	.	1	100	0	.	0	.	0	.	0	.	7	90	65	43	134	47	7	79	0	.	14	53	97	37	167	36	226	20	515	16	381	23	0	.	23	71	0	.	76	36	0	.	0	.	0	.	0	.	0	.	9	137	95	38	19	52	0	.	18	72	21	58	5	73	3	100	0	.	0	.	0	.	0	.	0	.	12	61	84	43	3	71	0	.	0	.	0	.	82	29	81	36	87	33	4	64	0	.	0	.	84	34	11	73	22	54	14	67	28	51	171	39	17	60	52	53	69	49	0	.	0	.	1	100	0	.	0	.	3	73	0	.	0	.	15	72	0	.	0	.	0	.	0	.	514	17	411	17	285	23	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	4415	6
	21-30 cm	0	.	0	.	0	.	0	.	3	.	0	.	1046	18	92	50	0	.	5	100	0	.	0	.	0	.	0	.	33	80	178	50	176	41	13	75	0	.	35	107	390	28	363	28	442	20	1100	16	726	19	0	.	69	83	0	.	206	49	0	.	0	.	0	.	0	.	0	.	55	55	233	39	62	44	0	.	43	74	76	56	18	73	-6	155	0	.	0	.	0	.	0	.	0	.	24	56	179	45	16	84	0	.	0	.	0	.	62	40	92	48	202	30	24	61	0	.	0	.	148	39	45	53	23	113	38	55	80	76	273	38	16	53	84	43	169	52	0	.	0	.	11	100	0	.	0	.	0	.	0	.	7	.	44	67	0	.	0	.	0	.	0	.	904	16	515	19	543	21	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	8855	5
	31-40 cm	0	.	0	.	0	.	0	.	4	.	0	.	1462	17	144	50	0	.	0	.	0	.	0	.	0	.	0	.	73	71	126	54	279	43	38	59	0	.	59	73	709	28	370	30	595	22	1813	14	1140	17	0	.	35	72	0	.	150	34	0	.	0	.	0	.	0	.	0	.	77	60	262	32	135	45	0	.	53	79	129	60	46	81	12	71	0	.	0	.	0	.	0	.	0	.	66	54	247	36	54	65	0	.	0	.	0	.	126	58	175	39	344	32	4	152	0	.	0	.	124	38	27	76	81	62	62	59	120	69	364	33	90	67	204	67	132	48	0	.	0	.	46	81	0	.	0	.	35	85	4	.	30	.	78	55	0	.	0	.	0	.	0	.	1147	16	753	20	728	20	21	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	12771	5
	41-50 cm	0	.	0	.	0	.	0	.	0	.	0	.	1829	16	143	44	0	.	0	.	0	.	0	.	0	.	0	.	71	81	133	53	233	40	26	62	0	.	56	50	781	23	518	24	1030	20	2039	13	1076	17	0	.	18	72	0	.	222	37	0	.	0	.	0	.	0	.	0	.	63	60	273	33	149	47	0	.	60	71	55	89	34	80	67	89	0	.	0	.	0	.	0	.	0	.	63	57	161	35	54	69	0	.	0	.	0	.	176	41	116	44	349	26	36	62	0	.	0	.	56	40	43	88	47	66	96	60	103	60	239	33	199	60	154	39	201	40	0	.	0	.	52	64	0	.	0	.	41	71	22	.	37	.	52	48	0	.	0	.	0	.	0	.	971	18	745	20	772	19	48	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	13710	5
	51-60 cm	0	.	0	.	0	.	0	.	0	.	0	.	1636	19	109	52	0	.	6	100	0	.	0	.	0	.	0	.	32	100	-4	100	86	68	96	80	0	.	80	65	781	25	527	25	894	20	1735	13	629	22	0	.	0	.	0	.	92	43	0	.	0	.	0	.	0	.	0	.	8	100	143	36	134	38	0	.	24	100	110	47	15	100	53	62	0	.	0	.	0	.	0	.	0	.	60	85	66	82	12	100	0	.	0	.	0	.	142	47	190	32	233	31	8	100	0	.	0	.	63	53	31	71	95	63	45	71	92	54	205	38	103	46	99	47	215	44	0	.	0	.	37	63	0	.	0	.	0	.	31	.	12	.	35	75	0	.	0	.	0	.	0	.	963	20	407	24	695	23	5	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	11029	5
	61-70 cm	0	.	0	.	0	.	0	.	0	.	0	.	399	23	61	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	44	73	44	83	0	.	137	69	341	29	355	34	577	24	867	21	191	44	0	.	0	.	0	.	57	71	0	.	0	.	0	.	0	.	0	.	10	100	142	41	76	52	0	.	0	.	16	100	25	77	32	100	0	.	0	.	0	.	0	.	0	.	16	100	31	71	0	.	0	.	0	.	0	.	177	49	160	54	115	50	21	71	0	.	0	.	11	100	28	73	36	76	14	100	82	100	62	75	45	80	88	53	30	72	0	.	0	.	24	100	0	.	0	.	0	.	0	.	0	.	14	100	0	.	0	.	0	.	0	.	449	29	221	39	388	29	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	5383	8
	71-80 cm	0	.	0	.	0	.	0	.	0	.	0	.	170	36	0	.	0	.	42	100	0	.	0	.	0	.	0	.	0	.	0	.	15	100	0	.	0	.	65	63	175	44	269	46	176	39	634	25	67	59	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	10	100	12	100	34	100	0	.	0	0	34	73	21	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	38	100	17	100	0	.	0	.	0	.	0	.	41	71	100	55	0	.	0	.	0	.	13	100	0	.	57	73	20	100	42	100	62	77	17	100	99	52	26	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	286	31	126	43	165	45	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	2833	11
	81-90 cm	0	.	0	.	0	.	0	.	0	.	0	.	138	54	0	.	0	.	27	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	42	71	0	.	31	100	53	71	82	58	107	65	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	24	100	0	.	0	.	45	71	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	15	100	0	.	25	100	0	.	0	.	0	.	61	74	0	.	0	.	0	.	0	.	33	100	15	100	47	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	103	50	46	71	53	59	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	947	18
	91-100 cm	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	47	71	0	.	44	100	0	.	32	100	17	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	24	100	0	.	0	.	38	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	32	100	48	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	20	100	31	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	0	21	100	26	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	381	29
	>100 cm	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	29	100	0	.	0	.	143	51	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	37	100	0	.	0	.	0	.	0	.	0	.	90	72	0	.	72	100	0	.	0	.	0	.	0	.	24	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	394	33
	total	0	.	0	.	0	.	0	.	9	.	0	.	7137	14	573	39	0	.	82	91	0	.	0	.	0	.	0	.	215	71	498	45	967	36	224	66	0	.	535	48	3303	19	2643	21	3992	16	8960	10	4334	14	0	.	145	74	0	.	803	31	0	.	0	.	0	.	0	.	0	.	232	52	1159	29	657	35	0	.	197	71	525	38	164	69	159	77	0	.	0	.	0	.	0	.	0	.	240	48	805	32	156	61	0	.	0	.	0	.	848	29	903	28	1455	24	98	60	0	.	0	.	649	29	186	57	434	52	287	55	566	50	1439	28	502	48	851	34	840	35	0	.	0	.	171	53	0	.	0	.	79	74	57	.	86	.	238	50	0	.	0	.	0	.	0	.	5337	13	3245	15	3654	15	74	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	60719	4
lower and upper montane	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	.
	12-20 cm	72	41	5	71	31	66	71	38	119	32	271	23	716	16	786	12	208	21	845	14	0	0	23	63	143	31	0	.	110	54	256	32	425	21	264	31	0	.	388	27	175	30	120	22	37	49	193	45	0	.	813	14	235	32	197	26	415	17	63	52	200	22	50	41	68	33	215	25	189	33	68	48	248	26	145	30	157	31	252	29	128	32	292	21	135	34	117	37	188	30	62	46	143	29	297	27	218	27	134	33	68	66	0	.	60	76	0	.	80	33	0	.	189	31	139	29	75	37	328	26	286	35	232	31	136	29	107	48	21	69	107	41	38	45	182	26	96	36	18	85	244	23	37	68	41	34	190	23	82	32	144	33	48	38	46	49	71	63	73	57	68	63	0	.	13	90	354	19	154	33	55	48	23	64	221	36	80	48	0	.	13	100	27	97	0	.	14427	3
	21-30 cm	113	39	3	100	69	59	174	50	459	27	837	21	1319	14	1814	12	625	21	1976	13	4	100	101	52	226	27	0	.	79	60	353	28	956	21	500	24	0	.	848	27	195	31	390	28	24	66	208	33	0	.	1647	13	328	28	331	27	1021	18	129	39	421	24	182	37	181	33	450	23	391	29	114	52	386	27	501	26	314	29	622	20	351	31	1059	19	273	35	179	38	345	25	59	57	439	25	327	26	415	25	267	27	305	33	0	.	32	60	0	.	98	39	0	.	260	33	260	26	122	39	271	26	264	37	264	26	227	38	40	74	8	72	180	34	84	47	355	26	247	37	37	100	503	23	82	67	148	37	473	21	171	27	278	28	89	40	49	46	145	45	83	46	87	62	0	.	6	100	504	21	261	30	168	40	17	135	520	27	313	28	0	.	15	100	4	100	0	.	28976	3
	31-40 cm	312	34	30	100	67	66	376	29	703	24	1253	20	2099	14	3348	11	1035	19	2773	13	35	83	149	51	352	27	0	.	134	49	451	34	1388	18	737	29	0	.	1017	24	335	27	453	24	29	58	161	38	0	.	2770	12	701	26	756	21	1503	19	173	38	508	24	367	41	211	30	827	22	506	29	192	39	599	25	768	22	495	37	826	20	437	24	1359	18	341	34	209	36	638	26	138	51	705	24	578	26	764	24	315	33	331	30	0	.	78	66	0	.	104	40	0	.	140	35	219	32	68	46	227	27	218	39	289	42	208	32	55	43	92	59	146	51	73	45	628	27	335	36	117	100	535	24	58	62	201	33	571	21	350	30	454	26	145	42	144	61	211	48	113	43	279	56	0	.	8	100	647	21	389	26	291	51	107	52	865	21	525	25	0	.	100	100	31	100	0	.	43276	3
	41-50 cm	282	36	16	100	7	100	369	33	484	27	1567	19	2615	13	4462	10	1499	17	2312	12	24	72	94	63	467	32	0	.	135	69	569	28	1145	18	837	27	0	.	908	20	304	34	518	26	76	62	81	46	0	.	2366	12	685	26	1093	22	1732	18	285	30	652	22	318	39	266	32	855	19	378	33	342	37	781	26	890	25	364	32	945	20	597	27	1831	18	111	45	370	29	432	30	296	43	571	25	821	24	965	26	441	25	418	30	0	.	51	59	0	.	134	41	0	.	105	46	181	36	58	40	201	31	169	33	142	31	129	44	53	55	26	77	183	36	172	53	505	29	473	31	62	86	445	24	81	66	300	34	564	21	364	28	471	33	320	32	161	54	251	44	165	45	318	44	0	.	0	.	401	25	479	31	314	42	237	38	882	23	523	28	0	.	18	100	59	100	0	.	46570	3
	51-60 cm	176	42	0	.	0	.	228	39	282	39	1007	21	2357	16	3588	11	1232	19	1355	17	92	100	100	61	419	32	0	.	157	60	319	33	964	22	380	32	0	.	549	24	255	34	482	27	19	72	145	44	0	.	1410	15	765	28	861	23	1360	19	148	39	404	27	184	53	191	43	986	21	277	34	219	36	591	33	537	31	263	37	819	27	431	28	1736	17	107	53	266	37	133	38	81	52	232	33	562	29	612	25	411	34	376	37	0	.	52	65	0	.	145	38	0	.	35	58	156	39	30	83	169	38	72	50	99	46	193	56	44	77	66	67	248	46	111	46	362	33	227	42	32	100	413	34	52	63	254	38	319	24	279	40	412	32	267	36	62	80	185	49	139	47	263	50	17	.	0	.	306	30	429	38	192	42	219	48	614	26	321	33	0	.	0	.	15	100	0	.	34869	3
	61-70 cm	17	100	0	.	0	.	35	100	105	60	220	35	1138	21	1964	14	737	22	492	25	26	100	37	72	116	69	0	.	0	.	184	41	429	31	131	43	0	.	254	34	160	43	161	34	0	.	54	54	0	.	685	23	440	36	380	27	357	33	100	60	148	37	31	71	165	41	347	26	0	.	123	53	211	43	249	35	248	54	262	36	197	40	735	28	46	72	101	73	57	58	38	71	29	100	280	40	339	36	466	33	84	60	0	.	84	78	0	.	116	61	0	.	23	73	34	99	0	.	81	44	39	72	61	46	96	71	64	100	33	100	123	42	63	71	131	40	293	45	41	100	160	42	29	100	231	43	16	100	196	43	75	50	70	50	0	.	88	81	62	58	49	77	20	.	0	.	81	56	220	39	104	69	43	71	281	38	60	58	0	.	0	.	0	.	0	.	15442	5
	71-80 cm	0	.	51	100	0	.	31	100	74	76	0	.	250	35	711	21	363	33	245	34	26	100	0	.	80	58	0	.	92	100	0	.	142	38	81	68	0	.	119	47	0	.	61	80	47	72	17	100	0	.	157	36	29	100	0	.	89	58	68	58	101	59	0	.	87	63	123	80	31	100	94	76	17	100	49	71	22	100	93	51	129	48	501	33	0	.	22	100	44	71	0	.	0	.	100	52	65	71	150	60	20	100	0	.	0	.	0	.	36	100	0	.	14	100	11	100	0	.	42	58	81	58	28	73	0	.	25	100	15	100	0	.	23	100	45	71	84	58	0	.	19	100	0	.	28	100	53	71	14	100	121	54	19	100	0	.	70	58	63	100	0	.	0	.	0	.	63	58	24	100	74	72	17	100	60	61	30	100	0	.	0	.	0	.	0	.	5440	8
	81-90 cm	0	.	0	.	0	.	0	.	0	.	43	100	119	55	509	27	58	71	36	100	0	.	0	.	32	100	0	.	0	.	31	100	0	.	0	.	0	.	25	100	0	.	28	100	12	100	43	74	0	.	92	58	23	100	0	.	0	.	0	.	0	.	32	100	0	.	30	100	0	.	0	0	0	.	0	.	56	71	29	100	0	.	193	46	0	.	0	.	0	.	0	.	28	100	29	100	29	100	62	74	0	.	0	.	0	.	0	.	45	77	0	.	0	.	0	.	0	.	51	63	0	0	0	.	0	.	0	.	24	100	86	74	31	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	50	72	0	.	0	.	0	.	31	100	0	.	0	.	0	.	0	.	0	.	1854	14
	91-100 cm	0	.	0	.	0	.	41	100	0	.	0	.	0	.	81	71	0	.	31	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	22	100	0	.	43	100	0	.	0	.	0	.	0	.	0	.	33	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	44	100	0	.	0	.	0	0	37	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	67	71	0	.	0	.	0	.	0	.	45	100	0	.	0	.	23	100	0	.	23	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	43	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	34	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	567	26
	>100 cm	0	.	0	.	0	.	0	.	0	.	0	.	118	59	47	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	18	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	0	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	19	100	0	.	0	.	0	.	0	.	0	.	0	.	232	100	0	.	0	.	31	100	0	.	48	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	513	50
	total	974	31	104	71	173	54	1324	29	2226	22	5197	17	10731	11	17310	8	5756	15	10064	10	206	81	504	44	1835	25	0	.	707	42	2164	24	5448	15	2953	21	0	.	4169	17	1424	23	2213	20	244	47	902	28	0	.	9972	10	3205	21	3618	18	6475	15	967	31	2433	18	1164	32	1169	27	3833	17	1773	24	1150	31	2833	23	3185	21	1919	28	3848	17	2270	22	7743	15	1013	30	1265	25	1836	21	674	38	2147	20	2994	20	3407	20	2333	23	1602	25	0	.	357	55	0	.	802	34	0	.	1000	32	1023	24	353	31	1423	19	1129	25	1162	25	990	31	388	47	285	58	1073	29	594	41	2208	23	1798	29	306	75	2321	19	339	59	1203	29	2187	16	1456	26	1956	22	957	28	461	46	1022	39	697	40	1064	41	38	.	26	95	2404	17	1957	25	1231	33	661	39	3474	18	1852	22	0	.	145	100	136	83	0	.	191934	2
submontane	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	.
	12-20 cm	272	19	403	26	380	32	258	24	0	.	0	.	62	44	144	30	1082	16	45	78	106	37	149	39	98	40	3	.	131	40	145	41	7	.	95	30	0	.	0	.	26	72	35	42	0	.	0	.	0	.	238	26	199	42	201	34	37	51	33	46	0	.	37	52	12	.	0	.	1	100	44	73	32	59	82	38	94	43	30	65	85	44	7	.	276	21	86	36	72	48	161	41	115	32	7	64	0	.	2	72	176	31	196	29	286	39	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	54	72	7	.	21	61	52	40	41	88	5	.	38	45	72	48	19	74	114	32	39	63	0	.	54	55	50	59	138	39	59	57	51	61	0	.	70	46	0	.	0	.	118	35	52	57	48	48	104	27	99	73	147	39	219	32	93	38	226	46	0	.	7939	5
	21-30 cm	650	18	393	23	474	25	530	22	0	.	0	.	198	48	348	26	2158	12	43	63	143	40	270	31	327	35	15	.	160	41	258	35	11	.	252	33	0	.	0	.	85	63	38	50	0	.	0	.	0	.	658	20	324	36	396	29	67	50	72	42	0	.	90	42	4	.	0	.	32	79	6	71	71	61	187	33	178	47	66	69	143	40	32	.	447	23	146	31	130	39	276	29	371	33	37	68	0	.	44	71	344	30	365	26	360	30	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	72	58	52	.	57	61	73	48	90	70	3	.	154	40	15	53	37	73	152	36	143	49	0	.	96	45	206	36	266	36	123	38	120	60	0	.	371	35	0	.	0	.	151	34	122	70	118	50	267	31	81	55	312	38	281	28	201	32	141	32	0	.	14905	4
	31-40 cm	1042	18	634	22	672	24	896	20	0	.	0	.	212	39	431	28	2552	11	59	59	253	33	391	31	488	27	26	.	457	32	316	34	75	.	506	27	0	.	11	.	70	72	99	54	0	.	0	.	0	.	932	22	572	33	702	24	38	83	101	42	0	.	117	48	41	.	0	.	91	71	44	100	68	72	404	39	209	46	114	51	237	43	12	.	825	22	378	33	310	43	380	29	441	28	67	92	0	.	126	65	455	31	456	29	647	26	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	20	80	46	.	48	59	116	49	66	63	13	.	231	58	64	64	24	77	427	36	140	47	0	.	131	43	210	37	403	28	183	43	74	47	0	.	406	33	0	.	0	.	38	96	60	49	199	44	618	29	95	53	412	28	358	28	541	28	379	32	0	.	22258	4
	41-50 cm	895	17	968	21	367	26	1365	20	0	.	0	.	473	40	473	33	3438	11	39	100	400	32	332	32	342	32	9	.	523	32	387	39	59	.	456	32	0	.	18	.	73	59	93	61	0	.	0	.	0	.	839	20	767	30	694	27	105	57	99	43	0	.	133	49	0	.	0	.	19	71	22	100	96	61	438	31	168	51	110	57	191	56	0	.	740	23	646	27	144	48	485	31	296	36	31	100	0	.	33	58	532	34	703	32	487	26	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	-4	100	32	.	15	100	86	50	77	75	28	.	214	42	209	50	72	75	295	34	47	74	0	.	52	86	206	41	344	36	125	54	105	59	0	.	367	39	0	.	0	.	62	60	98	66	339	35	699	25	193	52	463	29	592	27	545	26	580	29	0	.	24331	4
	51-60 cm	847	23	640	25	455	24	1016	21	0	.	0	.	248	39	384	36	3027	12	21	71	399	28	188	47	158	33	0	.	390	32	181	43	52	.	350	32	0	.	0	.	46	81	101	51	0	.	0	.	0	.	669	20	404	34	410	29	61	79	90	57	0	.	62	68	0	.	0	.	10	100	19	100	60	100	285	37	49	71	38	76	106	48	0	.	499	21	585	34	2	84	288	37	114	47	16	100	0	.	35	75	331	35	370	33	475	27	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	31	100	26	.	21	100	30	60	38	75	0	.	194	46	64	71	41	100	162	41	16	100	0	.	94	63	62	60	89	48	27	73	108	52	0	.	223	36	0	.	0	.	58	57	65	65	225	45	560	27	43	65	573	32	300	33	468	36	494	32	0	.	17494	4
	61-70 cm	393	31	225	34	169	40	532	27	0	.	0	.	61	59	218	47	1330	18	0	.	219	43	84	80	51	73	0	.	158	39	92	45	49	.	108	66	0	.	0	.	26	100	0	.	0	.	0	.	0	.	276	37	62	58	177	45	80	71	0	.	0	.	22	100	0	.	0	.	0	.	0	.	0	.	88	45	29	100	15	100	117	63	0	.	256	32	275	38	20	100	120	43	77	82	0	.	0	.	58	100	180	53	151	48	254	36	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	15	100	38	71	12	100	0	.	85	76	26	100	12	100	177	46	14	100	0	.	0	.	19	100	0	.	0	.	78	61	0	.	65	100	0	.	0	.	74	61	30	100	41	71	208	36	0	.	163	49	165	35	81	45	174	42	0	.	7450	7
	71-80 cm	94	61	89	67	42	71	137	51	0	.	0	.	0	.	146	81	635	25	0	.	97	77	0	.	0	.	0	.	0	.	48	100	0	.	54	73	0	.	0	.	0	.	23	100	0	.	0	.	0	.	73	58	0	.	65	71	0	.	0	.	0	.	17	100	0	.	0	.	0	.	0	.	0	.	0	.	64	82	14	100	79	100	0	.	0	.	210	56	0	.	25	100	0	.	0	.	0	.	29	100	60	57	33	100	146	48	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	15	100	0	.	0	.	0	.	0	.	0	.	23	100	0	.	0	.	167	48	0	.	0	.	0	.	0	.	20	100	0	.	0	.	0	.	42	73	0	.	0	.	0	.	0	.	0	.	85	77	24	100	58	72	0	.	105	61	25	100	0	.	2743	12
	81-90 cm	31	100	19	100	27	100	106	59	0	.	0	.	0	.	193	60	280	36	0	.	38	100	35	100	0	.	0	.	35	100	29	100	0	.	67	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	59	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	58	100	0	.	30	100	0	.	0	.	0	.	0	.	32	100	56	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	25	100	0	.	0	.	0	.	29	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	40	100	0	.	45	100	50	71	26	100	35	100	0	.	1345	18
	91-100 cm	0	.	62	71	0	.	0	.	0	.	0	.	0	.	0	.	124	58	0	.	49	100	0	.	0	.	0	.	0	.	0	.	0	.	41	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	46	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	322	36
	>100 cm	0	.	35	100	0	.	0	.	0	.	0	.	0	.	0	.	42	100	0	.	0	.	40	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	117	58
	total	4225	14	3470	17	2587	18	4841	16	0	.	0	.	1255	36	2337	24	14669	9	207	53	1704	25	1489	25	1463	26	53	.	1855	28	1455	28	254	.	1927	25	0	.	30	.	325	55	389	48	0	.	0	.	0	.	3686	16	2388	24	2646	22	387	54	395	37	0	.	478	43	57	.	0	.	153	71	134	80	327	60	1484	29	791	42	386	52	959	39	51	.	3042	17	2385	25	677	35	1765	25	1413	26	158	69	0	.	327	61	2110	25	2330	23	2700	20	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	189	61	163	.	178	60	396	41	324	55	50	.	940	38	449	45	205	59	1493	27	398	42	0	.	452	42	754	35	1260	26	516	36	564	42	0	.	1545	30	0	.	0	.	501	31	427	48	971	30	2581	22	534	45	2173	24	1965	22	2060	24	2054	24	0	.	98904	3
hyperinsubric and colline	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	.
	12-20 cm	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	149	42	0	.	4	.	0	.	15	100	212	27	4	79	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	18	.	9	100	18	175	25	56	160	37	246	25	750	16	153	36	173	38	273	24	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	16	.	0	.	0	.	22	89	0	.	0	.	17	.	0	.	0	.	0	.	143	30	85	37	24	63	0	.	0	.	0	.	0	.	0	.	12	71	0	.	0	.	0	.	2528	8
	21-30 cm	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	182	41	0	.	6	.	0	.	5	100	218	35	4	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	3	.	15	72	59	35	47	53	130	34	321	24	710	18	136	32	169	32	358	27	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	10	.	0	.	0	.	35	74	0	.	0	.	16	.	0	.	0	.	0	.	99	39	90	43	40	47	0	.	0	.	0	.	0	.	0	.	48	76	0	.	0	.	0	.	2703	8
	31-40 cm	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	66	56	0	.	8	.	0	.	0	.	164	42	10	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	3	100	30	78	26	86	112	40	152	36	461	21	91	47	94	37	239	28	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	16	71	0	.	0	.	0	.	0	.	0	.	0	.	131	35	56	45	50	63	0	.	0	.	0	.	0	.	0	.	73	78	0	.	0	.	0	.	1781	10
	41-50 cm	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	86	55	0	.	0	.	0	.	18	100	58	64	32	86	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	25	.	0	.	35	42	30	87	43	65	111	56	158	30	73	32	59	66	164	37	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	2	100	0	.	0	.	0	.	0	.	0	.	0	.	77	39	24	100	38	75	0	.	0	.	0	.	0	.	0	.	52	61	0	.	0	.	0	.	1085	13
	51-60 cm	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	65	84	0	.	0	.	0	.	14	100	93	84	12	72	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	31	63	13	71	45	72	60	46	96	42	81	51	33	75	146	45	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	49	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	54	62	0	.	0	.	0	.	0	.	0	.	0	.	0	.	14	100	0	.	0	.	0	.	806	19
	61-70 cm	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	12	100	0	.	0	.	0	.	7	100	13	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	13	100	17	71	14	78	10	100	30	70	26	72	31	58	11	100	45	51	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	9	100	15	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	253	21
	71-80 cm	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	15	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	68	47	10	100	0	.	32	100	52	51	10	100	11	100	43	61	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	15	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	256	25
	81-90 cm	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	20	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	102	57	15	100	0	.	0	.	28	71	14	100	0	.	35	72	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	60	100	0	.	0	.	0	.	274	34
	91-100 cm	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	32	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	97	67	0	.	0	.	6	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	136	54
	>100 cm	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	47	72	0	.	0	.	139	100	43	100	325	59	0	.	105	58	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	657	38
	total	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	560	36	0	.	18	.	0	.	59	73	826	27	63	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	.	0	.	46	.	39	86	406	38	180	64	501	30	1092	25	2420	14	913	30	549	29	1414	22	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	75	.	0	.	0	.	75	71	0	.	0	.	33	.	0	.	0	.	0	.	513	30	270	34	167	47	0	.	0	.	0	.	0	.	0	.	259	61	0	.	0	.	0	.	10479	6
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	.
	12-20 cm	345	17	408	26	411	30	330	20	121	31	271	23	1405	11	954	11	1290	14	890	14	106	37	172	35	241	24	3	.	248	32	465	22	569	19	366	24	149	42	414	26	388	18	378	19	393	15	1123	12	950	13	1051	12	458	25	398	21	533	14	95	38	200	22	88	32	80	31	215	25	228	30	231	26	338	21	227	23	278	23	317	25	218	25	311	20	410	18	203	26	260	26	223	32	258	21	318	26	302	23	139	32	244	29	196	29	364	34	95	27	225	23	154	24	362	23	385	19	824	15	594	18	474	25	534	18	205	27	151	36	222	32	190	27	133	36	265	22	134	29	89	42	264	22	166	28	80	35	193	22	158	28	194	29	206	28	121	36	122	45	73	57	139	39	888	12	717	13	916	12	206	29	103	34	127	25	320	33	227	30	231	30	106	35	253	42	0	.	31417	2
	21-30 cm	763	17	396	23	543	23	703	20	462	26	837	21	3165	9	2258	11	2783	11	2024	12	146	39	371	26	553	23	15	.	272	31	789	20	1143	19	765	19	182	41	914	25	997	16	957	16	804	16	2227	11	1870	11	2305	11	721	22	728	20	1305	16	202	29	421	24	272	29	184	32	450	23	515	24	392	29	637	20	688	21	544	24	850	17	513	24	1082	19	720	19	325	25	474	21	336	26	810	20	398	22	593	22	327	25	650	22	365	26	395	28	92	32	355	20	313	23	421	23	581	18	832	16	613	17	495	23	665	18	340	29	206	43	367	31	282	25	288	30	564	24	401	27	52	73	552	22	244	32	291	30	473	21	302	23	492	22	405	26	188	29	266	36	83	46	457	31	1644	12	1239	13	1667	13	383	30	287	31	284	30	601	24	625	23	330	26	217	30	145	31	0	.	61179	2
	31-40 cm	1355	16	664	21	739	23	1272	16	707	24	1253	20	4630	9	3967	10	3587	9	2832	13	288	30	540	26	840	19	26	.	663	25	892	22	1742	16	1281	20	66	56	1204	21	1493	16	1129	16	1196	16	2970	10	2729	11	3702	11	1308	20	1457	16	1709	17	275	28	508	24	484	33	252	30	827	22	711	23	543	23	905	19	1172	20	770	27	1181	17	720	21	1383	17	1167	18	588	25	948	23	517	25	1146	18	764	22	1011	20	495	27	786	22	456	29	725	24	193	41	464	21	472	26	257	26	371	24	529	19	515	18	368	26	609	24	290	27	260	39	507	27	394	30	393	38	785	23	566	32	181	68	605	22	486	32	341	27	606	20	501	24	694	21	642	21	328	36	285	38	113	43	685	30	2226	11	1469	14	2022	12	470	23	489	35	724	26	960	20	937	19	432	27	640	28	410	31	0	.	87796	2
	41-50 cm	1177	16	984	21	373	25	1734	17	484	27	1567	19	5693	9	5093	9	4937	9	2351	12	424	30	426	28	809	23	9	.	729	28	1089	21	1437	16	1320	20	86	55	1086	18	1667	15	1371	17	1810	14	3302	10	2956	9	3205	10	1469	20	1787	17	2062	16	383	25	652	22	450	31	266	32	855	19	463	28	685	23	1071	21	1328	19	600	25	1210	18	822	23	1898	17	851	21	1016	20	576	26	781	25	867	21	933	22	1126	22	529	22	950	23	703	32	564	24	243	33	495	21	446	23	189	32	293	31	216	24	431	19	304	26	354	23	230	36	238	37	300	28	496	29	452	28	830	21	688	25	271	43	569	22	376	30	346	31	606	20	441	26	714	25	739	22	286	38	356	36	165	45	685	29	2083	11	1540	14	1782	12	626	27	653	27	936	21	1074	21	985	20	644	25	563	25	639	28	0	.	94303	2
	51-60 cm	1024	20	640	25	455	24	1244	19	282	39	1007	21	4751	10	4102	11	4259	10	1382	17	491	30	288	37	577	25	0	.	579	28	496	26	1101	20	826	22	65	84	704	21	1484	17	1195	16	1381	15	2634	10	2001	12	2079	12	1169	22	1271	18	1512	17	238	33	404	27	245	43	191	43	986	21	335	31	395	24	821	26	822	24	347	30	1004	22	552	24	1782	17	606	20	852	26	134	38	369	31	346	27	674	25	679	24	458	31	707	26	370	33	527	25	255	34	539	19	298	26	89	44	216	31	126	38	415	22	144	34	340	29	270	43	204	36	304	31	467	30	242	31	618	26	422	31	95	58	492	30	263	34	270	36	319	24	404	32	486	29	407	27	89	60	293	36	139	47	486	31	1744	14	970	19	1419	15	500	33	417	31	778	23	657	25	894	24	314	32	468	36	509	31	0	.	70201	2
	61-70 cm	411	30	225	34	169	40	567	26	105	60	220	35	1906	14	2243	13	2067	14	492	25	244	40	121	59	167	53	0	.	158	39	276	31	522	28	282	35	12	100	425	31	759	19	603	23	792	19	1352	16	534	22	961	20	501	33	556	24	493	27	100	60	148	37	53	59	165	41	347	26	29	58	278	32	312	32	337	28	303	46	329	31	339	32	767	28	301	29	376	34	77	50	158	37	106	66	326	36	371	33	525	31	264	41	151	48	338	33	248	37	373	31	156	40	53	45	64	62	26	72	159	29	95	42	142	32	126	57	158	66	109	53	205	33	201	34	256	32	377	39	67	72	196	37	206	42	245	41	16	100	196	43	94	45	84	45	0	.	166	52	62	58	114	66	1034	19	409	25	665	21	250	36	146	53	251	32	281	38	222	39	165	35	81	45	174	42	0	.	31540	3
	71-80 cm	94	61	141	56	42	71	168	45	74	76	0	.	512	23	856	22	999	20	288	33	122	64	0	.	80	58	0	.	92	100	48	100	157	36	135	50	0	.	223	33	297	32	353	38	343	28	790	21	278	27	230	31	29	100	65	71	89	58	68	58	101	59	17	100	87	63	123	80	41	80	122	61	81	60	49	71	86	66	158	36	229	45	501	33	0	.	232	51	44	71	25	100	0	.	134	43	103	58	196	49	80	50	33	100	146	48	49	59	208	31	153	46	14	100	43	79	52	51	119	36	92	52	128	41	53	58	67	73	76	65	74	59	121	46	71	58	107	50	0	.	19	100	167	48	28	100	53	71	14	100	121	54	38	71	0	.	70	58	63	100	42	73	662	20	154	38	270	32	24	100	74	72	102	66	83	52	89	58	0	.	105	61	25	100	0	.	12795	5
	81-90 cm	31	100	19	100	27	100	106	59	0	.	43	100	314	33	702	26	338	32	63	71	38	100	35	100	32	100	0	.	35	100	61	71	0	.	67	100	0	.	84	51	27	100	87	53	118	42	145	42	214	40	92	58	82	77	0	.	0	.	0	.	0	.	32	100	0	.	30	100	0	.	0	0	24	100	0	.	56	71	87	52	0	.	193	46	0	.	58	100	0	.	30	100	28	100	29	100	29	100	62	74	32	100	56	100	0	.	30	71	186	42	59	59	0	.	0	.	28	71	126	45	0	0	35	72	0	.	0	.	57	71	102	65	78	72	18	100	0	.	0	.	0	.	0	.	0	.	0	.	25	100	0	.	0	.	0	.	29	100	0	.	0	.	226	32	99	52	103	46	0	.	0	.	40	100	31	100	45	100	110	63	26	100	35	100	0	.	4990	8
	91-100 cm	0	.	62	71	0	.	41	100	0	.	0	.	18	100	81	71	124	58	31	100	49	100	0	.	0	.	0	.	0	.	0	.	0	.	63	74	0	.	110	52	0	.	44	100	33	100	65	71	45	58	33	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	24	100	44	100	0	.	66	72	0	0	37	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	67	71	0	.	0	.	46	100	58	71	93	71	0	.	0	.	23	100	97	67	23	100	0	.	6	100	0	.	20	100	31	100	0	.	0	.	0	.	43	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	85	51	21	100	26	100	0	.	34	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	1643	15
	>100 cm	0	.	35	100	0	.	0	.	0	.	0	.	118	59	47	100	42	100	0	.	0	.	40	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	72	79	29	100	0	.	33	100	161	47	64	59	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	0	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	19	100	0	.	0	.	0	.	37	100	47	72	0	.	232	100	139	100	43	100	446	46	0	.	225	47	0	.	0	.	0	.	0	.	24	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	53	73	17	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	1922	21
	total	5199	13	3574	17	2760	18	6165	14	2235	22	5197	17	22512	8	20305	8	20425	7	10353	10	1910	24	1993	22	3298	18	53	.	2776	22	4116	17	6672	14	5104	16	560	36	5236	15	7141	11	6117	12	6903	12	14768	8	11641	8	13658	8	5738	16	6264	14	7704	13	1361	24	2433	18	1642	26	1226	26	3833	17	2321	20	2646	19	4214	17	4668	17	2984	21	5202	14	3393	19	7953	14	4055	15	3649	18	2513	18	2440	21	3560	16	3575	18	4213	17	2817	20	3713	18	2330	23	3103	18	1299	22	2985	15	2050	19	1617	22	2115	17	2773	13	3441	13	1972	17	3038	16	1514	24	1303	30	1975	23	2209	20	1931	22	3408	18	2738	23	755	41	2697	18	1907	24	1601	24	2266	16	2041	21	2795	18	2520	17	1011	28	1586	29	697	40	2609	24	10645	9	6637	11	8871	9	2459	22	2202	22	3242	19	4008	17	4025	17	2225	21	2205	23	2191	23	0	.	397785	1

Table citation

Abegg, M.; Ahles, P.; Allgaier Leuch, B.; Cioldi, F.; Didion, M.; Düggelin, C.; Fischer, C.; Herold, A.; Meile, R.; Rohner, B.; Rösler, E.; Speich, S.; Temperli, C.; Traub, B.,
2023: Swiss national forest inventory - Result table No. 2281792. Birmensdorf, Swiss Federal Research Institute WSL

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