Selection from the list of topics

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

1. What do the numbers stand for?

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

Example 1: Estimated value and standard error

NFI5

volume of deadwood (stemwood)
ownership (2 categories)

regional demarcation: production region

unit: m³/ha

evaluation area: accessible forest without shrub forest

grid: 1.4 km grid, subgrids 1-5

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

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

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2. What is the purpose of the standard error?

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

The statistical certainty is:

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

Example 2: Calculating confidence intervals

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

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

Procedure

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

Answer

			Step 1	Step 2

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

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

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

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

Data: see example 2

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

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

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3. When are two results statistically different?*

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

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

Example 4: Interpretation of two results from the same inventory

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

	case 2						case 1

case 1

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

Procedure

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

Answer

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

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

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

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

Case 2

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

Procedure

See case 1.

Answer

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

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

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

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

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

Example 5: Interpretation of two results from different inventories

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

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

Procedure

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

Answer

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

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

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

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

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

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

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

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

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

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

Procedure

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

Answer

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

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

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

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

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

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

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

Procedure

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

Answer

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

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

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

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

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

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

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

Example 8: Standard error and combination of variable expressions

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

The standard error increases as the level of detail increases.

Large standard errors are to be expected if:

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

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

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

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5. Two types of changes?

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

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

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

The results are:

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

Example 9: : Additivity/non-additivity of changes

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

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

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

Example 10: Average number of years per domain

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

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

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

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

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

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

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

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

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

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

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NFI3
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 2004/06
		forest district (2024)
		AG01		AG02		AG03		AG04		AI01		AR01		BE01		BE02		BE03		BE04		BSBL01		BSBL02		BSBL03		BSBL04		FR01		FR02		FR03		FR04		GE01		GL01		GR01		GR02		GR03		GR04		GR05		JU01		LU01		LU02		LU03		NE01		NE02		NE03		NE04		NE06		NW01		OW01		OW02		SG01		SG02		SG03		SG04		SG05		SH01		SO01		SO02		SO03		SO04		SZ01		SZ02		SZ03		TG01		TG02		TG03		TI01		TI02		TI03		TI04		TI05		TI06		TI07		TI08		TI09		UR01		UR02		UR03		VD02		VD03		VD04		VD05		VD06		VD07		VD08		VD09		VD11		VD12		VD14		VD15		VD16		VD18		VD20		VD22		VS01		VS02		VS03		ZG01		ZH01		ZH02		ZH03		ZH04		ZH05		ZH06		ZH07		lakes		Switzerland
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	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	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	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	31-40 cm	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	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	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.
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	.	4	71	2	100	0	.	18	29	262	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	.	3	100	13	51	19	52	0	.	0	.	0	.	23	57	5	.	0	.	0	.	0	.	3	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	137	38	61	32	9	62	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	560	13
	21-30 cm	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	22	88	21	100	10	.	57	36	489	17	0	.	0	.	0	.	0	.	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	100	21	76	20	78	0	.	0	.	0	.	26	68	0	.	0	.	0	.	0	.	19	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	229	28	96	32	27	72	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	1043	11
	31-40 cm	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	21	71	4	100	6	.	166	39	634	19	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	.	5	255	13	100	0	.	0	.	0	.	13	100	0	.	0	.	0	.	0	.	2	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	268	23	211	37	21	71	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	1370	12
	41-50 cm	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	11	71	8	100	0	.	155	38	575	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	.	30	54	9	71	6	.	0	.	0	.	22	100	0	.	0	.	0	.	0	.	11	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	373	23	112	32	14	77	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	1325	11
	51-60 cm	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	14	100	15	100	0	.	140	35	553	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	.	8	100	17	71	17	71	0	.	0	.	0	.	16	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	201	29	53	42	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	1034	15
	61-70 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	.	59	65	136	33	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	36	75	11	100	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	.	139	30	85	40	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	510	18
	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	.	41	59	186	37	0	.	0	.	0	.	0	.	0	.	0	.	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	100	0	.	0	.	0	.	19	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	133	36	14	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	407	22
	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	.	59	59	66	64	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	14	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	.	50	58	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	189	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	.	0	.	43	74	0	.	0	.	0	.	0	.	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	.	38	71	19	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	111	42
	>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	.	19	100	45	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	.	0	.	0	.	0	.	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	72	16	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	125	42
	total	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	103	75	51	100	17	.	715	28	2990	14	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	.	27	76	136	45	103	46	6	.	0	.	0	.	133	58	5	.	0	.	0	.	0	.	34	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	1614	18	667	26	70	62	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	6676	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	.	187	22	0	0	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	18	.	0	.	0	.	36	58	140	29	64	41	197	32	245	23	322	22	0	.	0	.	0	.	12	72	0	.	0	.	0	.	0	.	0	.	33	77	17	77	41	71	0	.	9	100	32	45	0	.	11	.	0	.	0	.	0	.	0	.	0	.	7	67	0	.	0	.	0	.	0	.	0	.	17	53	52	38	33	48	8	100	0	.	0	.	47	37	12	63	12	93	0	.	3	76	22	78	18	69	7	62	4	63	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	4	.	0	.	0	.	0	.	0	.	201	18	148	26	195	28	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	2151	7
	21-30 cm	0	.	0	.	0	.	0	.	0	.	0	.	558	19	9	72	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	27	.	0	.	0	.	56	66	266	29	155	33	320	28	569	19	766	17	0	.	0	.	0	.	17	76	0	.	0	.	0	.	0	.	0	.	64	77	30	96	100	51	0	.	3	100	89	57	0	.	11	.	0	.	0	.	0	.	0	.	0	.	6	100	0	.	0	.	0	.	0	.	0	.	11	106	119	39	74	62	17	77	0	.	0	.	66	46	21	84	9	100	6	.	30	69	11	71	61	57	4	100	34	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	2	.	0	.	0	.	0	.	0	.	373	25	456	22	452	31	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	4790	7
	31-40 cm	0	.	0	.	0	.	0	.	0	.	0	.	942	18	37	81	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	77	67	498	25	221	43	508	26	952	19	934	17	0	.	0	.	0	.	17	100	0	.	0	.	0	.	0	.	0	.	21	72	36	52	163	53	0	.	-13	100	93	46	0	.	-1	.	0	.	0	.	0	.	0	.	0	.	52	68	0	.	0	.	0	.	0	.	0	.	78	47	191	36	82	43	3	100	0	.	0	.	106	46	31	56	11	100	0	.	49	64	6	100	37	71	43	61	13	58	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	18	.	0	.	0	.	0	.	0	.	585	20	675	23	625	23	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	7090	6
	41-50 cm	0	.	0	.	0	.	0	.	0	.	0	.	825	19	18	71	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	132	51	456	25	196	30	746	21	1110	19	1430	14	0	.	0	.	0	.	7	100	0	.	0	.	0	.	0	.	0	.	21	74	49	62	108	58	0	.	7	100	80	71	0	.	0	.	0	.	0	.	0	.	0	.	0	.	29	100	0	.	0	.	0	.	0	.	0	.	72	53	155	36	94	49	6	100	0	.	0	.	128	47	35	55	0	.	0	.	46	82	18	78	43	89	69	45	54	72	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	22	.	0	.	0	.	0	.	0	.	719	20	659	22	662	22	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	7996	6
	51-60 cm	0	.	0	.	0	.	0	.	0	.	0	.	609	20	74	72	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	76	54	573	26	109	40	587	23	690	19	1033	15	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	41	80	16	72	35	73	0	.	24	100	55	40	0	.	0	.	0	.	0	.	0	.	0	.	0	.	40	76	0	.	0	.	0	.	0	.	0	.	150	39	220	33	74	54	0	.	0	.	0	.	95	42	17	80	0	0	17	.	56	72	13	100	69	78	31	59	50	82	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	19	.	0	.	0	.	0	.	0	.	784	20	582	26	443	26	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	6582	6
	61-70 cm	0	.	0	.	0	.	0	.	0	.	0	.	344	28	28	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	46	59	290	30	59	55	296	33	390	28	463	24	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	36	74	16	100	11	100	0	.	10	100	22	73	0	.	0	.	0	.	0	.	0	.	0	.	0	.	32	100	0	.	0	.	0	.	0	.	0	.	62	45	64	53	40	59	0	.	0	.	0	.	51	62	0	0	0	.	0	.	13	100	0	.	64	88	25	72	68	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	7	.	0	.	0	.	0	.	0	.	560	27	253	42	136	43	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	3386	9
	71-80 cm	0	.	0	.	0	.	0	.	0	.	0	.	191	39	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	22	100	223	41	16	100	151	42	91	46	151	40	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	10	100	15	100	0	.	14	100	14	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	21	100	0	.	0	.	0	.	0	.	0	.	107	47	32	71	69	78	0	.	0	.	0	.	49	58	11	100	0	.	20	.	0	.	0	.	44	82	36	71	15	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	357	31	16	100	139	44	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	1811	12
	81-90 cm	0	.	0	.	0	.	0	.	0	.	0	.	46	71	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	37	72	65	71	22	100	74	72	39	71	53	71	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	22	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	16	100	42	100	20	100	0	.	0	.	0	.	0	0	0	.	0	.	0	.	0	.	0	.	13	100	0	.	22	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	266	33	36	71	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	772	19
	91-100 cm	0	.	0	.	0	.	0	.	0	.	0	.	20	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	20	100	0	.	18	100	54	74	28	100	41	71	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	17	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	26	100	22	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	.	246	31
	>100 cm	0	.	0	.	0	.	0	.	0	.	0	.	20	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	33	100	0	.	0	.	31	100	0	.	21	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	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	0	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	131	46
	total	0	.	0	.	0	.	0	.	0	.	0	.	3742	16	167	67	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	45	.	0	.	0	.	535	44	2510	20	860	27	2966	17	4114	15	5212	12	0	.	0	.	0	.	53	84	0	.	0	.	0	.	0	.	0	.	216	55	174	51	495	44	0	.	53	85	428	40	0	.	21	.	0	.	0	.	0	.	0	.	0	.	186	65	0	.	0	.	0	.	0	.	0	.	538	32	896	28	484	38	34	71	0	.	0	.	541	33	127	47	32	97	42	.	197	62	70	63	350	56	216	41	260	72	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	72	.	0	.	0	.	0	.	0	.	3844	16	2825	20	2652	19	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	34955	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	.	6	.	0	.	375	18	17	64	0	.	2	100	0	.	0	.	0	.	0	.	6	74	76	48	29	48	4	77	0	.	30	47	67	33	196	24	450	19	670	15	293	19	0	.	21	71	0	.	77	38	0	.	0	.	0	.	0	.	0	.	18	52	99	32	19	56	0	.	16	72	11	52	8	69	0	0	0	.	0	.	0	.	0	.	0	.	-2	361	57	34	2	177	0	.	0	.	0	.	141	33	85	36	151	26	3	53	0	.	0	.	87	36	11	70	37	61	9	78	22	46	90	36	31	66	58	44	59	43	0	.	0	.	0	.	0	.	0	.	4	72	0	.	0	.	9	66	0	.	0	.	0	.	0	.	460	17	533	18	320	18	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	4659	5
	21-30 cm	0	.	0	.	0	.	0	.	8	.	0	.	876	17	44	67	0	.	0	.	0	.	0	.	0	.	0	.	16	100	165	51	92	41	20	71	0	.	55	72	224	27	400	28	442	19	1143	15	728	18	0	.	43	71	0	.	151	53	0	.	0	.	0	.	0	.	0	.	33	63	272	38	48	53	0	.	39	73	59	47	16	83	0	0	0	.	0	.	0	.	0	.	0	.	25	65	85	58	9	73	0	.	0	.	0	.	156	34	164	39	183	26	22	63	0	.	0	.	158	38	35	64	29	72	22	89	90	52	255	31	45	47	104	48	177	55	0	.	0	.	9	100	0	.	0	.	0	.	0	.	18	76	38	93	0	.	0	.	0	.	0	.	889	16	759	18	648	21	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	8792	5
	31-40 cm	0	.	0	.	0	.	0	.	0	.	0	.	1213	21	168	50	0	.	9	100	0	.	0	.	0	.	0	.	54	75	169	50	196	66	25	75	0	.	21	97	616	26	479	28	588	21	1828	14	1206	19	0	.	51	85	0	.	130	32	0	.	0	.	0	.	0	.	0	.	34	74	267	34	120	47	0	.	54	72	125	71	29	100	-36	100	0	.	0	.	0	.	0	.	0	.	108	47	164	44	47	52	0	.	0	.	0	.	93	41	183	49	313	33	38	45	0	.	0	.	185	34	56	73	57	70	67	58	131	69	333	38	37	74	216	56	160	43	0	.	0	.	4	100	0	.	0	.	39	78	5	100	26	82	53	65	0	.	0	.	0	.	0	.	1104	17	737	19	706	23	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	12209	5
	41-50 cm	0	.	0	.	0	.	0	.	5	.	0	.	1631	16	149	43	0	.	0	.	0	.	0	.	0	.	0	.	72	73	190	54	244	38	66	63	0	.	82	62	826	29	451	25	852	20	2012	13	1172	17	0	.	42	75	0	.	211	38	0	.	0	.	0	.	0	.	0	.	20	64	201	36	113	39	0	.	63	71	92	72	51	75	86	75	0	.	0	.	0	.	0	.	0	.	84	53	200	38	54	62	0	.	0	.	0	.	44	55	228	33	416	31	38	61	0	.	0	.	161	32	30	82	37	94	89	50	121	65	251	36	145	71	201	44	223	39	0	.	0	.	16	88	0	.	0	.	37	71	16	100	41	80	81	76	0	.	0	.	0	.	0	.	797	17	949	20	696	20	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	13587	5
	51-60 cm	0	.	0	.	0	.	0	.	0	.	0	.	1943	22	92	61	0	.	6	100	0	.	0	.	0	.	0	.	40	73	35	64	179	51	66	73	0	.	86	50	679	25	507	27	1006	20	1860	14	730	22	0	.	-3	100	0	.	151	43	0	.	0	.	0	.	0	.	0	.	16	100	225	38	135	43	0	.	16	100	72	73	10	100	143	57	0	.	0	.	0	.	0	.	0	.	80	67	88	69	24	100	0	.	0	.	0	.	106	38	149	38	303	31	34	62	0	.	0	.	83	44	49	76	97	64	49	63	101	58	185	38	224	47	219	42	249	35	0	.	0	.	40	71	0	.	0	.	15	71	43	71	36	84	47	61	0	.	0	.	0	.	0	.	1028	18	540	20	773	23	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	12557	6
	61-70 cm	0	.	0	.	0	.	0	.	0	.	0	.	705	23	54	61	0	.	0	.	0	.	0	.	0	.	0	.	18	100	0	.	16	100	72	65	0	.	154	60	436	33	300	39	608	24	1011	19	196	37	0	.	0	.	0	.	54	50	0	.	0	.	0	.	0	.	0	.	12	100	100	43	38	59	0	.	9	100	9	100	29	77	19	100	0	.	0	.	0	.	0	.	0	.	54	66	72	78	0	.	0	.	0	.	0	.	152	52	140	43	207	36	25	71	0	.	0	.	26	71	12	100	67	84	13	100	30	71	155	62	81	52	113	46	175	58	0	.	0	.	19	100	0	.	0	.	0	.	23	100	16	100	27	100	0	.	0	.	0	.	0	.	664	28	349	27	418	34	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	6676	7
	71-80 cm	0	.	0	.	0	.	0	.	0	.	0	.	299	28	25	100	0	.	22	100	0	.	0	.	0	.	0	.	0	.	0	.	56	100	23	100	0	.	134	65	191	42	296	47	310	30	671	27	154	43	0	.	0	.	0	.	19	100	0	.	0	.	0	.	0	.	0	.	29	100	74	67	30	71	0	.	0	.	57	71	23	100	38	100	0	.	0	.	0	.	0	.	0	.	30	74	0	.	18	100	0	.	0	.	0	.	68	58	142	56	83	46	0	0	0	.	0	.	0	0	24	100	68	59	37	72	97	82	140	52	32	100	125	47	40	72	0	.	0	.	24	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	384	29	164	45	353	35	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	4283	9
	81-90 cm	0	.	0	.	0	.	0	.	0	.	0	.	96	58	0	.	0	.	55	100	0	.	0	.	0	.	0	.	0	.	0	.	20	100	0	.	0	.	48	71	56	71	96	77	84	60	334	31	120	57	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	24	100	0	.	0	.	31	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	21	100	24	100	56	71	0	.	0	.	0	.	63	73	0	.	27	100	0	.	43	100	0	.	19	100	121	63	29	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	182	45	124	45	64	59	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	1734	14
	91-100 cm	0	.	0	.	0	.	0	.	0	.	0	.	95	74	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	62	71	30	100	0	.	63	71	71	71	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	31	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	22	100	0	.	0	.	0	.	42	100	0	.	0	.	0	.	26	100	0	.	0	.	32	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	31	100	50	71	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	555	25
	>100 cm	0	.	0	.	0	.	0	.	0	.	0	.	51	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	38	100	42	100	0	.	153	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	.	71	100	32	100	0	.	0	.	0	.	0	.	38	100	0	.	78	100	0	.	0	.	32	100	0	.	21	100	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	.	580	29
	total	0	.	0	.	0	.	0	.	20	.	0	.	7284	15	549	42	0	.	94	92	0	.	0	.	0	.	0	.	204	71	635	43	833	37	277	58	0	.	672	47	3162	20	2766	21	4404	15	9753	10	4600	14	0	.	155	75	0	.	792	32	0	.	0	.	0	.	0	.	0	.	163	55	1237	30	558	35	0	.	197	70	458	46	166	69	248	64	0	.	0	.	0	.	0	.	0	.	380	43	666	35	154	57	0	.	0	.	0	.	852	27	1148	27	1733	22	161	49	0	.	0	.	843	26	216	56	496	52	286	52	662	46	1441	29	615	46	1209	31	1111	33	0	.	0	.	113	62	0	.	0	.	95	71	86	78	137	75	254	51	0	.	0	.	0	.	0	.	5539	13	4204	14	4004	15	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	65633	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	89	52	2	100	14	66	80	37	124	34	180	28	735	18	651	12	193	27	624	13	0	.	12	56	117	28	0	.	33	50	108	30	292	24	174	31	0	.	285	22	167	28	113	24	32	50	185	29	0	.	717	15	193	26	170	27	407	17	25	48	204	21	33	49	108	38	225	25	146	35	57	38	240	36	96	38	180	30	163	28	107	43	275	25	136	41	105	32	173	28	44	57	104	28	233	26	187	27	150	29	149	40	0	.	59	57	0	.	85	39	0	.	202	27	206	26	59	42	340	20	330	29	199	27	101	35	99	51	9	179	58	40	45	42	215	26	102	41	0	.	203	25	50	92	49	41	197	22	87	44	128	31	31	42	52	71	66	54	29	45	43	76	8	.	18	72	423	20	140	30	45	45	9	57	110	50	92	55	0	.	34	74	25	91	0	.	12789	3
	21-30 cm	106	42	4	100	43	60	198	41	370	27	746	21	1207	13	1631	12	553	26	1766	13	6	100	57	52	280	28	0	.	130	57	252	30	639	19	497	29	0	.	1062	27	369	26	222	32	15	77	253	28	0	.	1370	12	333	27	423	29	990	19	123	52	364	25	185	37	128	34	378	22	360	31	82	45	492	23	442	27	318	29	607	21	356	35	869	19	285	38	152	36	346	28	102	47	329	28	429	24	461	26	204	33	330	35	0	.	54	52	0	.	167	36	0	.	290	27	256	34	118	44	453	26	348	31	270	25	262	37	75	51	21	61	269	40	72	41	295	31	259	34	0	.	554	22	98	65	133	35	490	21	163	29	284	32	76	43	124	44	102	54	60	53	69	60	16	.	21	77	618	19	228	33	138	43	31	63	423	26	262	29	0	.	35	100	44	81	0	.	28041	3
	31-40 cm	232	33	12	100	48	68	300	37	786	24	1119	20	1794	14	2584	11	827	24	2246	12	37	100	129	48	342	28	0	.	81	64	528	26	1225	22	581	27	0	.	1034	22	402	29	546	23	31	63	264	33	0	.	2682	12	482	27	459	25	1223	18	148	38	549	23	306	36	252	29	697	21	424	32	141	45	413	25	651	23	464	27	825	21	469	26	1179	18	418	31	274	36	488	24	63	50	702	27	463	24	475	26	444	27	431	28	0	.	78	69	0	.	94	42	0	.	229	37	246	30	85	58	314	23	171	31	301	33	275	36	93	57	69	61	321	32	80	46	611	25	127	36	6	100	589	21	67	69	148	39	700	20	247	33	537	26	113	45	118	47	265	44	97	46	79	65	20	.	4	100	771	20	288	28	297	37	80	50	658	23	554	29	0	.	89	100	19	100	0	.	39106	3
	41-50 cm	300	35	32	77	28	71	299	35	698	25	1401	20	2444	14	3582	10	1348	19	2698	12	41	100	57	64	535	27	0	.	134	45	419	29	959	20	877	26	0	.	1219	22	361	29	636	24	45	55	143	32	0	.	2710	12	599	25	748	26	1724	17	279	32	645	22	292	38	209	33	811	21	231	33	141	35	600	27	861	24	403	33	932	22	576	31	1581	19	166	45	288	31	337	27	164	50	621	23	720	25	763	25	513	25	407	29	0	.	75	63	0	.	131	38	0	.	136	42	201	29	50	57	235	31	241	33	211	31	84	54	41	54	69	67	304	39	96	63	633	29	325	35	43	100	576	23	85	61	200	38	655	19	407	28	455	25	195	33	186	60	232	48	171	45	148	57	0	.	0	.	535	23	581	27	215	42	170	52	810	21	566	26	0	.	44	100	28	100	0	.	44709	2
	51-60 cm	142	40	0	.	0	.	292	37	586	27	1563	27	2377	16	3962	12	1175	20	1548	20	0	.	113	78	501	33	0	.	110	62	483	29	714	21	619	29	0	.	914	21	316	34	466	28	50	60	159	48	0	.	1623	15	562	28	776	24	1388	20	154	34	613	24	223	40	269	37	986	19	192	45	147	46	508	27	414	29	155	39	934	24	688	27	1647	17	111	48	286	36	344	38	152	47	396	32	586	26	606	29	466	32	442	41	0	.	41	73	0	.	241	40	0	.	66	53	192	43	57	68	192	30	161	37	128	38	136	48	50	63	36	85	240	42	164	53	631	28	377	36	0	.	449	30	74	58	244	38	416	23	276	34	486	27	300	40	67	84	172	43	274	41	211	55	0	.	0	.	392	25	415	32	325	44	176	51	731	25	324	33	0	.	12	100	34	100	0	.	38849	3
	61-70 cm	135	52	0	.	0	.	140	68	145	39	850	25	1155	21	1982	13	843	21	842	22	0	.	94	59	244	56	0	.	61	73	212	42	262	40	248	39	0	.	173	32	180	37	357	30	9	100	94	52	0	.	716	21	613	31	438	31	573	23	67	50	237	32	75	80	179	44	594	22	76	51	158	46	387	38	399	36	176	62	340	35	128	37	1110	22	16	100	139	52	86	65	17	100	80	67	368	32	288	31	401	37	223	51	0	.	98	61	0	.	101	53	0	.	21	71	61	50	0	.	131	33	57	51	87	41	116	62	13	100	37	71	145	51	124	54	192	44	245	44	0	0	227	46	89	76	119	47	64	50	341	41	205	38	43	66	0	.	187	51	41	71	120	85	0	.	0	.	166	45	351	37	159	63	79	67	345	32	82	58	0	.	0	.	16	100	0	.	19972	4
	71-80 cm	0	.	0	.	0	.	24	100	72	77	0	.	490	30	1160	17	407	31	258	37	0	.	0	.	51	71	0	.	32	100	107	62	123	54	86	65	0	.	272	39	59	73	142	49	62	71	58	61	0	.	473	28	135	52	158	49	216	40	150	57	120	71	15	100	138	52	201	36	29	100	69	100	62	71	102	50	79	79	121	64	250	49	534	29	31	100	24	100	53	71	45	73	0	.	173	44	97	62	290	39	61	72	0	.	57	100	0	.	22	100	0	.	0	.	43	59	0	.	72	51	46	71	37	59	0	.	51	100	44	100	67	58	18	100	102	51	191	55	0	.	117	45	0	.	54	100	50	71	62	72	67	72	50	71	0	.	110	80	65	100	22	100	0	.	0	.	51	60	103	59	62	72	23	100	75	58	95	50	0	.	0	.	0	.	0	.	8787	6
	81-90 cm	0	.	0	.	0	.	36	100	29	100	35	100	184	49	434	32	135	50	96	58	0	.	0	.	0	.	0	.	39	100	34	100	55	71	62	100	0	.	40	76	0	.	33	100	0	.	20	100	0	.	245	77	0	.	0	.	28	100	24	100	67	71	36	100	0	.	175	68	0	.	35	100	61	100	32	100	0	.	0	.	65	72	235	71	0	.	0	.	113	100	0	.	38	100	103	58	27	100	111	59	0	.	0	.	0	.	0	.	36	100	0	.	11	100	0	.	0	.	80	72	32	100	0	.	0	.	0	.	25	100	39	100	21	100	25	100	30	100	0	.	0	.	0	.	92	74	34	100	0	.	63	71	0	.	0	.	28	100	39	100	0	.	0	.	0	.	58	61	31	100	22	100	27	100	25	100	0	.	0	.	0	.	0	.	0	.	3346	13
	91-100 cm	0	.	33	100	0	.	37	100	0	.	0	.	40	100	126	58	35	100	38	100	0	.	0	.	0	.	0	.	36	100	0	.	0	.	0	0	0	.	0	0	0	.	0	.	0	.	49	73	0	.	78	71	26	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	30	100	0	.	0	0	135	58	0	.	0	.	0	.	0	.	0	.	0	.	0	.	49	100	0	.	0	.	0	.	0	.	138	51	0	.	0	.	0	0	0	.	0	.	0	0	0	.	0	.	0	.	0	.	0	.	31	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	81	72	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	963	20
	>100 cm	0	.	0	.	0	.	0	.	0	0	0	.	61	100	53	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	68	75	0	.	0	.	0	.	0	.	0	.	36	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	51	100	0	.	0	.	0	.	55	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	24	100	0	.	0	.	0	.	0	.	0	.	0	.	432	100	0	.	0	.	30	100	0	.	29	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	.	841	54
	total	1003	31	82	71	132	60	1405	27	2810	22	5895	17	10488	11	16163	9	5517	16	10116	10	83	100	461	51	2070	26	0	.	655	43	2144	24	4270	16	3144	21	0	.	5068	19	1853	22	2514	19	244	46	1226	25	0	.	10651	10	2941	21	3171	20	6549	15	970	29	2800	18	1166	31	1283	26	4067	17	1459	26	831	37	2764	21	3048	20	1806	24	3924	17	2638	22	7620	15	1164	29	1269	26	1939	22	586	39	2269	22	3074	19	2904	21	2652	23	2043	25	0	.	462	54	0	.	1014	31	0	.	1389	34	1206	23	370	34	1848	19	1386	23	1263	22	974	30	424	38	311	57	1443	27	651	40	2703	22	1656	30	49	100	2714	19	463	60	1038	33	2606	16	1583	25	2225	21	808	29	547	43	1160	39	777	39	691	45	45	.	43	76	3095	17	2136	24	1263	32	595	44	3177	18	1975	23	0	.	214	95	166	71	0	.	197403	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	264	23	303	23	223	28	214	24	0	.	0	.	44	36	135	31	779	13	47	84	77	45	102	36	75	33	0	.	55	36	124	37	6	.	157	33	0	.	2	.	27	55	21	61	0	.	0	.	0	.	222	22	107	35	252	28	12	80	29	73	0	.	20	58	3	.	0	.	3	100	30	.	43	54	87	37	102	51	27	62	73	44	0	.	274	27	97	38	9	204	103	34	41	69	22	73	0	.	1	100	174	30	227	28	363	30	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	24	79	1	100	2	124	69	38	57	56	13	79	27	83	46	57	1	73	76	53	55	62	0	.	75	51	30	57	127	36	66	50	19	42	0	.	32	52	0	.	0	.	121	33	30	50	67	49	154	36	31	68	111	37	178	35	81	34	164	38	0	.	6635	4
	21-30 cm	528	20	393	24	462	26	459	26	0	.	0	.	164	43	357	31	1846	13	73	68	162	34	212	35	229	31	8	.	189	44	192	36	14	.	225	32	0	.	0	.	38	80	30	92	0	.	0	.	0	.	518	22	258	32	390	27	90	59	37	54	0	.	32	52	7	.	0	.	9	100	39	.	73	63	189	37	171	38	52	59	141	48	0	.	581	23	144	37	122	40	220	35	309	34	37	65	0	.	19	78	260	32	419	26	309	34	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	101	79	39	100	51	60	163	44	75	56	9	100	97	60	62	46	37	73	104	33	130	47	0	.	113	45	100	42	242	33	118	45	94	58	0	.	124	38	0	.	0	.	152	42	64	47	116	47	200	30	96	77	261	31	295	32	186	38	319	33	0	.	13352	4
	31-40 cm	848	27	492	22	617	23	544	23	0	.	0	.	227	38	323	25	2143	12	51	84	233	30	375	29	415	31	29	.	212	34	287	37	42	.	391	30	0	.	0	.	56	60	70	58	0	.	0	.	0	.	715	22	382	37	567	30	40	107	77	49	0	.	133	52	10	.	0	.	80	84	0	.	55	74	332	40	207	51	83	74	155	43	16	.	580	23	255	30	211	37	311	31	426	29	99	89	0	.	92	67	369	35	376	29	501	24	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	49	74	15	100	64	68	140	41	58	71	25	100	261	56	54	61	15	100	230	38	160	50	0	.	84	57	200	39	356	33	181	40	144	53	0	.	319	47	0	.	0	.	117	40	91	53	150	47	463	33	59	64	264	31	311	28	341	37	250	33	0	.	17827	4
	41-50 cm	881	20	713	25	525	27	846	20	0	.	0	.	389	42	427	32	2594	12	39	85	228	33	286	31	355	34	33	.	335	39	278	40	71	.	343	32	0	.	8	.	78	75	69	54	0	.	0	.	0	.	841	21	559	40	555	27	57	58	82	59	0	.	142	47	-1	.	0	.	23	97	0	.	47	78	333	32	229	45	79	53	284	52	0	.	999	22	487	28	278	40	363	31	307	34	31	100	0	.	61	61	368	45	530	28	528	25	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	-19	100	67	100	37	67	145	51	62	57	35	83	188	51	59	48	43	70	424	36	92	54	0	.	35	70	277	37	324	32	263	40	224	59	0	.	331	37	0	.	0	.	56	53	69	69	279	38	452	24	70	59	363	31	420	29	444	30	425	31	0	.	20847	4
	51-60 cm	688	21	698	23	463	24	1201	21	0	.	0	.	289	36	415	36	3070	13	11	100	358	35	261	42	185	38	0	.	327	41	193	40	20	.	381	31	0	.	0	.	62	59	60	51	0	.	0	.	0	.	623	25	310	36	654	33	91	51	71	47	0	.	96	66	0	.	0	.	11	100	0	.	88	86	302	34	74	54	92	69	134	48	0	.	499	25	715	29	62	54	258	37	223	42	4	100	0	.	64	80	163	43	468	35	442	28	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	30	100	10	100	0	.	40	63	132	82	14	100	175	51	51	68	54	85	218	37	22	71	0	.	59	52	111	54	175	38	44	60	128	48	0	.	279	49	0	.	0	.	28	72	41	100	321	34	469	27	84	63	488	32	538	35	306	35	512	35	0	.	18453	4
	61-70 cm	443	29	178	34	245	37	463	29	0	.	0	.	114	64	253	45	1453	17	0	.	265	39	159	53	126	51	18	.	94	54	38	74	59	.	133	75	0	.	0	.	14	100	0	.	0	.	0	.	0	.	194	38	286	41	195	48	93	71	34	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	124	48	26	100	19	100	91	60	0	.	331	37	321	44	30	72	54	59	68	59	15	100	0	.	79	100	36	71	179	45	254	40	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	13	100	0	.	0	.	16	100	19	100	0	.	44	71	24	100	0	.	200	44	0	.	0	.	42	100	16	100	46	74	19	100	135	49	0	.	228	48	0	.	0	.	52	56	21	100	146	48	218	42	15	100	128	54	144	49	117	41	286	37	0	.	8409	7
	71-80 cm	163	51	70	58	90	51	239	44	0	.	0	.	23	100	91	80	711	25	0	.	25	100	0	.	57	75	0	.	27	100	18	100	27	.	93	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	18	100	0	.	82	71	26	100	0	.	0	.	46	71	0	.	0	.	0	.	0	.	0	.	44	71	41	71	45	72	51	71	0	.	88	50	297	36	0	.	41	100	0	.	0	.	0	.	44	100	0	.	133	53	228	52	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	17	100	24	100	9	100	40	71	0	.	0	.	60	100	0	.	0	.	230	46	0	.	0	.	0	.	19	100	0	.	0	.	40	73	0	.	21	100	0	.	0	.	0	.	0	.	34	100	186	52	30	100	113	64	48	71	119	53	93	51	0	.	3905	10
	81-90 cm	81	77	27	100	28	100	31	100	0	.	0	.	0	.	112	58	86	58	0	.	0	0	36	100	0	.	0	.	31	100	0	.	0	.	0	.	0	.	0	.	0	.	31	100	0	.	0	.	0	.	0	.	0	.	32	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	48	100	0	.	0	.	80	100	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	.	57	73	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	30	100	0	.	47	100	41	75	27	100	0	.	0	.	851	21
	91-100 cm	24	100	0	.	0	.	39	100	0	.	0	.	0	.	0	.	210	51	0	.	50	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	.	72	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	35	100	0	.	0	.	0	.	35	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	38	100	0	.	0	.	0	.	0	.	27	100	0	.	530	30
	>100 cm	0	.	31	100	0	.	0	.	0	.	0	.	0	.	37	100	0	.	0	.	0	.	47	100	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	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	155	51
	total	3920	17	2905	17	2653	19	4036	17	0	.	0	.	1249	36	2150	24	12891	9	221	53	1398	26	1477	26	1442	26	87	.	1270	30	1131	30	239	.	1763	25	0	.	9	.	274	51	282	49	0	.	0	.	0	.	3132	17	1901	28	2727	23	408	50	328	37	0	.	470	45	19	.	0	.	126	75	69	.	306	63	1412	28	850	35	397	52	978	36	16	.	3352	16	2396	24	712	35	1350	24	1374	25	208	65	0	.	360	61	1368	31	2403	23	2652	19	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	216	71	156	99	163	59	612	37	404	50	96	90	852	43	297	41	151	59	1538	27	460	40	0	.	443	40	752	36	1271	26	691	35	818	43	0	.	1334	36	0	.	0	.	527	29	316	52	1113	30	2211	22	385	48	1774	26	1976	23	1622	26	2075	25	0	.	90964	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	.	63	42	0	.	0	.	0	.	15	100	222	32	6	82	0	.	0	.	0	.	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	.	14	71	58	59	50	52	235	31	160	32	603	18	161	29	182	38	292	27	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	8	76	0	.	0	.	26	.	0	.	0	.	0	.	84	34	74	35	44	38	0	.	0	.	0	.	0	.	0	.	4	100	0	.	0	.	0	.	2353	8
	21-30 cm	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	169	46	0	.	14	.	0	.	11	100	238	33	16	71	0	.	0	.	0	.	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	.	19	100	101	38	40	70	123	42	305	25	738	19	174	28	287	35	363	25	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	37	74	0	.	0	.	13	.	0	.	0	.	0	.	110	37	133	39	27	52	0	.	0	.	0	.	0	.	0	.	38	102	0	.	0	.	0	.	2967	8
	31-40 cm	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	155	43	0	.	10	.	15	.	0	.	213	27	3	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	.	12	73	52	42	46	51	138	42	245	32	608	21	50	122	115	33	269	29	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	27	77	0	.	0	.	3	.	0	.	0	.	0	.	129	39	104	38	56	49	0	.	0	.	0	.	0	.	0	.	49	100	0	.	0	.	0	.	2301	9
	41-50 cm	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	117	60	0	.	0	.	0	.	4	100	26	110	20	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	.	8	.	4	100	47	35	29	71	31	63	208	37	351	33	83	48	93	40	200	36	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	57	43	58	55	36	128	0	.	0	.	0	.	0	.	0	.	47	64	0	.	0	.	0	.	1421	13
	51-60 cm	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	30	85	0	.	0	.	8	.	13	100	63	52	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	.	12	.	0	.	35	60	13	70	71	57	95	43	139	41	117	36	60	67	125	48	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	85	57	0	.	27	71	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	911	15
	61-70 cm	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	31	71	0	.	0	.	0	.	11	100	99	82	7	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	.	14	100	26	73	8	100	27	73	66	42	67	52	18	72	18	71	81	71	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	9	100	18	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	500	23
	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	.	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	.	0	.	53	52	12	100	0	.	42	72	29	59	41	64	0	.	28	77	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	219	27
	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	.	73	52	15	100	0	.	15	100	37	73	15	100	0	.	15	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	11	100	0	.	0	.	0	.	0	.	0	.	35	100	0	.	0	.	0	.	216	31
	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	.	17	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	.	29	100	0	.	0	.	0	.	16	100	0	0	0	.	37	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	.	33	100	0	.	0	.	0	.	132	47
	>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	.	42	71	0	.	0	.	143	100	52	78	303	62	0	.	66	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	.	0	.	0	.	606	41
	total	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	565	39	0	.	24	.	23	.	55	75	891	26	72	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	.	83	.	63	81	516	30	213	51	625	28	1281	24	2640	14	962	27	755	28	1475	21	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	72	73	0	.	0	.	42	.	0	.	0	.	0	.	475	31	388	33	202	46	0	.	0	.	0	.	0	.	0	.	206	72	0	.	0	.	0	.	11627	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	353	21	305	23	236	26	294	20	129	33	180	28	1341	11	803	11	972	12	673	14	77	45	113	32	192	21	0	.	94	28	308	22	345	21	334	22	63	42	353	19	404	17	396	16	695	16	1340	11	883	11	939	12	321	20	422	20	508	15	54	45	204	21	53	38	111	37	225	25	200	29	202	25	343	27	184	27	307	25	233	22	188	30	286	25	411	22	202	24	181	28	146	29	145	28	259	24	244	22	153	28	323	24	227	28	474	26	174	27	293	20	252	20	448	20	366	20	663	17	658	14	541	22	540	18	134	31	126	41	126	32	176	24	168	27	291	21	129	37	46	57	205	25	125	49	105	38	201	21	171	32	159	27	171	28	144	39	85	43	29	45	75	49	891	12	834	13	1112	11	170	26	112	34	163	34	141	42	203	32	182	34	115	33	188	35	0	.	29147	2
	21-30 cm	634	18	396	24	504	24	656	22	379	27	746	21	2805	9	2041	11	2399	12	1839	13	168	33	269	30	509	21	8	.	335	33	609	22	773	17	742	22	169	46	1172	25	933	15	828	18	799	16	2260	10	1999	10	1888	10	633	20	813	20	1247	17	159	42	364	25	217	32	135	33	378	22	466	27	423	28	713	19	631	22	530	22	806	18	514	28	880	19	865	20	297	26	468	23	322	28	638	22	496	22	546	24	232	29	590	24	419	26	375	29	193	30	572	19	317	23	452	21	561	21	856	17	877	16	690	22	670	17	391	32	234	32	356	25	537	25	255	28	514	27	356	30	62	46	601	21	202	36	263	29	490	21	313	24	402	25	358	26	255	30	195	39	60	53	192	33	1616	11	1466	12	1924	12	292	28	254	32	232	28	518	25	523	21	333	30	222	36	363	31	0	.	58986	2
	31-40 cm	1080	22	504	22	665	22	845	20	786	24	1119	20	4176	10	3111	10	2970	11	2306	11	270	29	503	25	757	21	29	.	346	28	984	20	1463	21	997	20	155	43	1132	21	1603	15	1334	16	1133	16	3424	9	2777	11	3397	11	916	22	1025	20	1410	16	225	30	549	23	440	30	262	28	697	21	560	27	444	25	756	20	982	21	711	23	1126	18	653	22	1157	19	998	18	529	24	699	20	374	27	1128	20	722	22	639	23	583	24	799	22	376	29	579	23	182	29	526	23	454	25	410	25	491	22	693	19	669	18	374	21	638	21	390	28	288	38	473	29	535	23	397	34	809	21	387	39	60	56	608	21	297	33	308	32	739	19	363	27	762	21	540	24	303	30	409	34	97	46	398	40	2106	11	1731	13	2296	12	379	25	447	29	544	29	717	22	818	22	360	28	430	36	268	31	0	.	79903	2
	41-50 cm	1181	17	745	24	553	26	1145	17	703	25	1401	20	5289	9	4176	10	3943	10	2737	11	269	32	343	28	890	21	33	.	541	28	887	22	1274	17	1285	20	117	60	1441	20	1733	17	1361	15	1648	14	3447	10	3198	9	3551	10	1199	23	1303	19	1998	15	361	28	645	22	434	30	207	33	811	21	295	28	391	24	868	21	1195	20	701	25	1183	19	911	26	1667	18	1166	20	775	21	615	23	527	26	928	19	864	22	963	21	628	22	775	26	530	28	611	23	120	38	592	18	548	25	218	30	410	23	401	30	630	18	399	23	448	23	154	43	276	41	386	27	639	28	428	27	945	22	513	29	102	50	635	21	509	31	292	31	693	18	457	26	772	20	622	22	449	34	456	38	171	45	479	31	1946	11	1778	13	1998	12	649	25	494	28	622	23	881	20	929	20	467	27	488	28	453	30	0	.	89885	2
	51-60 cm	830	19	698	23	463	24	1494	18	586	27	1563	27	5218	11	4544	11	4246	11	1565	19	358	35	374	38	685	26	0	.	476	32	711	22	913	19	1066	21	30	85	1076	19	1643	15	1165	17	1657	15	2912	10	2335	11	2246	13	868	22	1429	20	1629	18	225	27	613	24	319	34	269	37	986	19	261	36	388	28	766	22	717	22	269	29	1154	21	831	23	1789	17	610	22	1000	23	406	33	410	29	619	25	710	23	694	27	554	29	604	32	468	35	496	26	263	27	662	20	406	25	171	33	287	32	195	35	502	18	286	29	350	28	232	35	218	36	235	33	573	28	546	31	943	21	552	29	51	68	543	27	292	31	266	35	432	22	378	28	633	23	542	26	111	56	300	32	274	41	490	37	2099	12	1174	16	1664	14	456	30	646	28	646	24	815	23	812	23	538	35	318	34	546	33	0	.	78387	2
	61-70 cm	578	25	178	34	245	37	603	27	145	39	850	25	2317	13	2318	12	2296	13	842	22	265	39	253	40	370	40	18	.	172	40	250	37	337	36	453	32	31	71	372	30	950	19	717	22	924	19	1653	15	802	18	910	18	898	25	633	26	720	21	100	47	237	32	75	80	179	44	594	22	124	39	274	31	436	34	523	30	221	51	391	32	248	30	1128	22	347	36	460	34	116	52	71	51	148	45	469	27	360	29	480	35	258	45	179	45	352	33	228	37	366	25	266	30	73	41	127	32	67	52	242	25	87	39	235	37	141	52	56	50	192	52	307	34	280	32	435	34	289	39	24	100	246	43	289	38	119	47	64	50	405	36	237	34	122	43	19	100	322	36	41	71	348	43	1372	18	705	21	773	22	372	35	305	40	296	36	360	31	209	40	144	49	117	41	302	36	0	.	39452	3
	71-80 cm	163	51	70	58	90	51	263	41	72	77	0	.	1003	18	1276	17	1117	19	281	35	25	100	0	.	108	52	0	.	59	71	125	55	206	44	202	55	0	.	428	33	472	27	454	34	524	23	874	22	491	23	492	27	135	52	240	40	261	35	150	57	120	71	61	59	138	52	201	36	58	71	153	56	107	48	145	41	134	52	238	40	324	40	572	28	119	45	321	34	53	71	86	61	0	.	224	36	97	62	352	35	61	72	133	53	284	46	175	36	249	36	179	38	0	0	86	46	29	59	180	31	81	52	134	38	74	51	172	57	193	44	183	37	179	37	158	39	252	48	0	.	141	41	230	46	54	100	50	71	62	72	86	60	50	71	0	.	150	62	65	100	43	71	874	19	194	40	543	26	103	59	97	58	209	47	106	50	208	42	48	71	119	53	93	51	0	.	19412	4
	81-90 cm	81	77	27	100	28	100	66	71	29	100	35	100	326	34	545	28	221	38	150	52	0	0	36	100	0	.	0	.	70	71	34	100	75	59	62	100	0	.	126	42	121	50	182	49	158	46	452	26	239	37	245	77	0	.	32	100	28	100	24	100	67	71	36	100	0	.	175	68	0	.	35	100	107	65	32	100	0	.	31	100	113	59	235	71	0	.	80	100	113	100	0	.	38	100	103	58	27	100	111	59	0	.	0	.	26	100	37	71	188	38	90	52	11	100	15	100	37	73	157	47	32	100	42	74	0	.	43	100	25	100	71	64	142	56	76	58	30	100	0	.	0	.	57	73	92	74	34	100	0	.	63	71	0	.	0	.	28	100	39	100	0	.	498	25	159	38	134	40	31	100	22	100	56	71	25	100	47	100	76	61	27	100	0	.	0	.	7108	8
	91-100 cm	24	100	33	100	0	.	75	71	0	.	0	.	155	54	126	58	245	46	38	100	50	100	0	.	0	.	0	.	36	100	0	.	0	.	0	0	0	.	82	59	30	100	18	100	117	51	165	42	84	51	78	71	26	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	31	100	0	.	30	100	17	100	0	0	135	58	0	.	0	.	0	.	0	.	0	.	0	.	0	.	49	100	0	.	72	100	0	.	37	76	189	42	22	100	0	.	0	0	16	100	42	100	0	0	37	100	0	.	26	100	0	.	0	.	63	71	0	.	0	.	0	.	0	.	0	.	0	.	0	.	35	100	0	.	0	.	0	.	35	100	0	.	0	.	69	59	69	58	81	72	0	.	0	.	38	100	0	.	0	.	33	100	0	.	27	100	0	.	2538	12
	>100 cm	0	.	31	100	0	.	0	.	0	0	0	.	132	62	90	72	0	.	0	.	0	.	47	100	0	.	0	.	0	.	0	.	0	.	41	100	0	.	101	60	38	100	42	100	31	100	172	47	65	59	36	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	51	100	0	.	27	100	0	.	55	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	24	100	0	.	0	.	0	.	71	100	74	59	0	.	432	100	143	100	52	78	371	52	0	.	173	55	0	.	0	.	32	100	0	.	21	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	46	72	16	100	26	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	2439	23
	total	4924	15	2987	17	2785	18	5441	14	2830	22	5895	17	22763	8	19029	8	18408	8	10431	10	1481	25	1938	23	3512	18	87	.	2129	23	3909	17	5386	15	5184	16	565	39	6284	16	7927	11	6496	12	7686	11	16699	7	12873	8	13783	8	4997	17	5898	15	7803	13	1298	23	2800	18	1636	25	1301	26	4067	17	1964	21	2310	21	4129	17	4460	17	2905	19	5206	14	3782	18	7906	15	4516	14	3666	18	2651	19	1936	21	3643	16	3847	17	3570	18	3167	20	3411	19	2403	23	3196	18	1481	20	3710	14	2534	17	2215	23	2487	17	3010	13	4326	12	2490	16	3267	15	1517	24	1438	28	2019	23	3020	19	2479	20	4171	17	2508	25	346	38	2979	17	2001	25	1498	26	2702	15	2184	20	3114	17	2405	18	1280	27	1979	29	777	39	2025	28	11517	8	8126	10	10550	9	2452	22	2375	22	2806	20	3563	17	3749	17	2182	22	1837	26	2241	24	0	.	407258	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. 2280595. Birmensdorf, Swiss Federal Research Institute WSL

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