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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NFI5
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, subgrids 1-5
state 2018/26
		forest district (2024)
		AG01		AG02		AG03		AG04		AI01		AR01		BE01		BE02		BE03		BE04		BSBL01		BSBL02		BSBL03		BSBL04		FR01		FR02		FR03		FR04		GE01		GL01		GR01		GR02		GR03		GR04		GR05		JU01		LU01		LU02		LU03		NE01		NE02		NE03		NE04		NE06		NW01		OW01		OW02		SG01		SG02		SG03		SG04		SG05		SH01		SO01		SO02		SO03		SO04		SZ01		SZ02		SZ03		TG01		TG02		TG03		TI01		TI02		TI03		TI04		TI05		TI06		TI07		TI08		TI09		UR01		UR02		UR03		VD02		VD03		VD04		VD05		VD06		VD07		VD08		VD09		VD11		VD12		VD14		VD15		VD16		VD18		VD20		VD22		VS01		VS02		VS03		ZG01		ZH01		ZH02		ZH03		ZH04		ZH05		ZH06		ZH07		lakes		Switzerland
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	.	15	62	0	.	8	100	67	32	319	21	0	.	0	.	0	.	0	.	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	.	34	67	38	61	6	82	0	.	0	.	9	135	4	.	1	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	211	52	48	57	7	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	771	18
	21-30 cm	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	6	100	0	.	12	83	211	42	585	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	.	56	62	23	117	70	100	0	.	0	.	8	100	21	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	211	40	98	41	20	77	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	1322	14
	31-40 cm	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	32	72	0	.	42	100	199	31	728	21	0	.	0	.	0	.	0	.	0	.	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	72	72	71	62	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	.	292	30	231	54	30	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	1729	14
	41-50 cm	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	28	80	0	.	15	100	192	36	820	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	.	36	80	19	74	0	.	0	.	0	.	0	.	0	.	21	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	314	34	229	44	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	1672	15
	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	.	19	100	185	36	554	26	0	.	0	.	0	.	0	.	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	.	35	60	16	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	.	223	38	67	53	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	1113	16
	61-70 cm	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	30	100	0	.	0	.	43	100	220	34	0	.	0	.	0	.	0	.	0	.	0	.	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	.	102	50	103	54	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	512	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	.	52	72	189	46	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	140	41	27	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	408	28
	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	.	76	71	197	61	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	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	22	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	341	41
	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	.	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	.	38	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	.	30	100	0	.	27	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	143	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	.	36	100	52	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	.	39	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	128	58
	total	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	111	69	0	.	96	66	1060	28	3713	16	0	.	0	.	0	.	0	.	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	.	202	54	182	60	176	81	0	.	0	.	17	103	25	.	22	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	1608	24	824	36	85	73	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	8138	10
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	.	276	22	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	31	.	0	.	0	.	44	75	200	28	31	38	106	32	171	35	411	30	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	61	97	39	63	75	66	0	.	0	.	13	86	0	.	16	.	0	.	0	.	0	.	0	.	0	.	21	77	0	.	0	.	0	.	0	.	0	.	37	54	86	47	56	64	2	100	0	.	0	.	69	39	20	70	23	.	0	.	21	88	59	64	8	100	10	63	7	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	3	.	0	.	0	.	0	.	0	.	332	29	195	30	129	42	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	2554	9
	21-30 cm	0	.	0	.	0	.	0	.	0	.	0	.	613	21	3	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	67	.	0	.	0	.	60	80	352	33	122	54	316	29	402	30	759	25	0	.	0	.	0	.	11	.	0	.	0	.	0	.	0	.	0	.	71	74	91	100	146	58	0	.	0	.	71	109	0	.	50	.	0	.	0	.	0	.	0	.	0	.	8	100	0	.	0	.	0	.	0	.	0	.	0	.	205	42	118	61	0	.	0	.	0	.	267	45	38	59	8	.	7	.	33	76	58	62	80	78	23	72	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	14	.	0	.	0	.	0	.	0	.	557	25	359	33	247	32	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	5156	8
	31-40 cm	0	.	0	.	0	.	0	.	0	.	0	.	1123	21	60	64	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	44	.	0	.	0	.	180	89	586	28	284	39	607	37	704	28	1061	21	0	.	0	.	0	.	9	.	0	.	0	.	0	.	0	.	0	.	97	84	88	76	275	66	0	.	0	.	292	61	0	.	10	.	0	.	0	.	0	.	0	.	0	.	30	71	0	.	0	.	0	.	0	.	0	.	78	70	294	38	57	59	53	100	0	.	0	.	153	36	14	60	6	.	13	.	117	72	45	73	80	73	43	60	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	673	32	378	28	437	32	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	7891	8
	41-50 cm	0	.	0	.	0	.	0	.	0	.	0	.	1538	21	32	74	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	22	.	0	.	0	.	279	64	683	25	373	39	695	33	654	29	1363	21	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	79	62	59	58	179	82	0	.	0	.	160	50	0	.	0	.	0	.	0	.	0	.	0	.	0	.	70	100	0	.	0	.	0	.	0	.	0	.	61	69	331	38	143	54	9	100	0	.	0	.	112	48	25	71	0	.	0	.	91	75	57	61	11	100	112	63	19	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	14	.	0	.	0	.	0	.	0	.	838	33	558	29	611	36	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	9178	8
	51-60 cm	0	.	0	.	0	.	0	.	0	.	0	.	889	24	53	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	93	54	799	26	153	55	591	29	471	32	1108	22	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	27	100	12	100	23	100	0	.	34	.	120	71	0	.	0	.	0	.	0	.	0	.	0	.	0	.	38	71	0	.	0	.	0	.	0	.	0	.	169	50	324	41	147	68	0	.	0	.	0	.	172	51	21	73	0	.	0	.	79	81	13	100	21	100	33	100	20	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	33	.	0	.	0	.	0	.	0	.	733	26	467	35	684	32	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	7325	8
	61-70 cm	0	.	0	.	0	.	0	.	0	.	0	.	510	30	39	71	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	82	74	303	42	73	58	545	37	242	37	785	33	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	70	75	22	100	71	100	0	.	14	.	0	0	0	.	0	.	0	.	0	.	0	.	0	.	0	.	110	79	0	.	0	.	0	.	0	.	0	.	120	52	90	62	67	58	0	.	0	.	0	.	92	62	21	100	0	.	36	.	69	76	0	.	0	.	34	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	12	.	0	.	0	.	0	.	0	.	718	30	326	42	365	38	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	4817	11
	71-80 cm	0	.	0	.	0	.	0	.	0	.	0	.	356	35	0	0	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	37	100	329	45	34	100	147	53	117	50	254	40	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	49	73	0	.	0	.	0	.	34	.	100	74	0	.	0	.	0	.	0	.	0	.	0	.	0	.	45	100	0	.	0	.	0	.	0	.	0	.	61	72	28	100	0	.	0	.	0	.	0	.	102	59	27	100	0	.	0	.	0	.	0	.	58	100	100	58	32	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	476	50	36	100	285	47	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	2709	15
	81-90 cm	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	107	59	261	67	91	71	96	76	61	71	140	78	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	30	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	43	100	0	.	0	.	0	.	0	.	0	.	79	100	0	.	0	.	0	.	0	.	0	.	67	71	28	100	0	.	23	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	384	44	34	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	1444	22
	91-100 cm	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	38	100	56	100	0	.	114	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	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	57	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	143	58	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	408	36
	>100 cm	0	.	0	.	0	.	0	.	0	.	0	.	36	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	155	71	82	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	38	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	.	311	47
	total	0	.	0	.	0	.	0	.	0	.	0	.	5340	18	187	74	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	166	.	0	.	0	.	921	48	3568	22	1163	36	3370	25	2904	24	5880	17	0	.	0	.	0	.	20	.	0	.	0	.	0	.	0	.	0	.	454	60	310	69	770	57	0	.	82	.	824	52	0	.	75	.	0	.	0	.	0	.	0	.	0	.	366	68	0	.	0	.	0	.	0	.	0	.	606	49	1357	32	587	48	63	97	0	.	0	.	1034	34	196	54	37	.	80	.	411	71	232	58	259	71	354	49	135	82	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	77	.	0	.	0	.	0	.	0	.	4854	20	2352	24	2758	26	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	41793	6
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	.	0	.	0	.	471	20	1	100	0	.	8	76	0	.	0	.	0	.	0	.	2	.	110	49	5	74	6	71	0	.	47	51	149	35	115	38	482	22	783	19	327	25	0	.	10	100	0	.	70	51	0	.	0	.	0	.	3	.	0	.	8	75	103	39	19	54	0	.	37	86	53	51	3	.	3	100	0	.	0	.	0	.	0	.	0	.	20	58	42	84	18	60	0	.	0	.	0	.	166	41	80	59	72	35	6	66	1	.	0	.	41	43	11	51	33	81	6	434	28	60	77	36	59	56	59	61	121	68	0	.	0	.	39	100	0	.	0	.	0	.	0	.	0	.	12	78	0	.	0	.	0	.	0	.	491	24	496	22	377	24	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	5070	6
	21-30 cm	0	.	0	.	0	.	0	.	0	.	0	.	655	20	5	100	0	.	0	.	0	.	0	.	0	.	0	.	6	.	177	59	23	73	6	100	0	.	67	61	224	41	524	39	878	22	1314	18	617	23	0	.	36	100	0	.	102	49	0	.	0	.	0	.	0	.	0	.	67	92	295	43	47	52	0	.	88	60	70	50	0	.	0	.	0	.	0	.	0	.	0	.	0	.	26	60	104	58	22	77	0	.	0	.	0	.	123	41	120	57	107	38	11	71	0	.	0	.	126	42	89	55	146	56	87	54	82	71	338	37	84	61	59	54	227	66	0	.	0	.	0	.	0	.	0	.	0	.	0	.	13	.	33	100	0	.	0	.	0	.	0	.	802	23	1200	24	869	27	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	9870	7
	31-40 cm	0	.	0	.	0	.	0	.	0	.	0	.	1217	19	101	66	0	.	10	100	0	.	0	.	0	.	0	.	34	.	314	51	39	66	78	71	0	.	84	70	409	32	549	34	650	23	1634	19	1162	24	0	.	49	100	0	.	94	52	0	.	0	.	0	.	0	.	0	.	14	100	294	41	113	49	0	.	85	71	56	55	31	.	10	100	0	.	0	.	0	.	0	.	0	.	104	59	123	68	38	100	0	.	0	.	0	.	154	54	104	54	285	50	52	72	0	.	0	.	274	41	67	60	149	58	72	72	181	71	345	40	155	51	135	56	165	57	0	.	0	.	17	100	0	.	0	.	0	.	0	.	9	.	53	82	0	.	0	.	0	.	0	.	1082	25	1101	23	998	26	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	12689	6
	41-50 cm	0	.	0	.	0	.	0	.	0	.	0	.	1261	21	172	66	0	.	1	100	0	.	0	.	0	.	0	.	67	.	297	50	117	56	75	73	0	.	126	71	970	32	370	30	722	26	2216	15	1514	21	0	.	13	100	0	.	131	54	0	.	0	.	0	.	0	.	0	.	21	100	213	45	134	53	0	.	141	72	26	100	85	.	0	0	0	.	0	.	0	.	0	.	0	.	210	58	64	100	89	71	0	.	0	.	0	.	166	52	107	55	388	40	33	75	0	.	0	.	163	45	87	65	130	65	123	74	293	85	275	50	256	71	423	59	201	55	0	.	0	.	0	0	0	.	0	.	0	.	0	.	0	.	42	72	0	.	0	.	0	.	0	.	1014	25	1040	24	927	22	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	14698	6
	51-60 cm	0	.	0	.	0	.	0	.	0	.	0	.	1607	22	44	73	0	.	11	100	0	.	0	.	0	.	0	.	111	.	136	54	121	66	115	71	0	.	76	51	795	31	257	42	1148	30	2047	18	1022	22	0	.	47	100	0	.	237	60	0	.	0	.	0	.	0	.	0	.	0	.	234	53	135	48	0	.	79	73	0	0	0	.	42	71	0	.	0	.	0	.	0	.	0	.	152	65	86	82	80	100	0	.	0	.	0	.	133	57	121	58	368	43	78	61	0	.	0	.	110	71	86	72	100	61	154	66	84	62	285	47	281	57	171	42	231	54	0	.	0	.	0	.	0	.	0	.	0	.	0	.	19	.	51	74	0	.	0	.	0	.	0	.	918	24	1003	25	888	30	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	13659	7
	61-70 cm	0	.	0	.	0	.	0	.	0	.	0	.	1094	23	45	100	0	.	0	.	0	.	0	.	0	.	0	.	35	.	0	.	46	100	26	100	0	.	179	71	420	36	237	52	542	38	1382	22	499	40	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	17	100	47	71	0	.	96	100	59	71	25	.	28	100	0	.	0	.	0	.	0	.	0	.	139	70	0	.	26	100	0	.	0	.	0	.	73	60	157	53	217	47	24	100	0	.	0	.	22	100	25	100	121	78	52	100	64	100	91	75	201	67	188	65	401	60	0	.	0	.	77	100	0	.	0	.	0	.	0	.	0	.	24	100	0	.	0	.	0	.	0	.	311	50	399	34	661	34	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	8051	9
	71-80 cm	0	.	0	.	0	.	0	.	0	.	0	.	779	29	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	29	100	85	100	0	.	299	62	230	45	59	100	551	34	537	31	155	51	0	.	0	.	0	.	28	100	0	.	0	.	0	.	0	.	0	.	0	.	91	58	108	72	0	.	0	.	0	.	0	.	37	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	195	83	203	84	192	50	25	100	0	.	0	.	29	100	58	71	65	100	30	100	0	.	125	72	68	71	87	71	0	.	0	.	0	.	54	100	0	.	0	.	0	.	0	.	0	.	28	100	0	.	0	.	0	.	0	.	361	45	227	50	459	37	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	5195	11
	81-90 cm	0	.	0	.	0	.	0	.	0	.	0	.	190	51	0	.	0	.	122	100	0	.	0	.	0	.	0	.	0	.	0	.	87	100	0	.	0	.	40	100	152	59	33	100	135	60	464	48	38	71	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	105	100	0	.	0	.	0	.	39	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	55	100	65	100	0	0	0	.	0	.	0	.	0	.	89	71	0	.	0	.	0	.	29	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	212	52	32	100	69	71	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	1953	19
	91-100 cm	0	.	0	.	0	.	0	.	0	.	0	.	171	58	0	.	0	.	71	100	0	.	0	.	0	.	0	.	0	.	0	.	72	100	0	.	0	.	116	71	41	100	131	71	0	.	184	58	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	55	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	77	100	0	.	0	.	0	.	0	.	0	.	0	.	48	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	52	100	136	58	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	1153	23
	>100 cm	0	.	0	.	0	.	0	.	0	.	0	.	0	0	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	51	100	0	.	0	.	0	.	197	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	.	129	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	49	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	64	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	491	40
	total	0	.	0	.	0	.	0	.	0	.	0	.	7443	16	369	60	0	.	224	93	0	.	0	.	0	.	0	.	255	.	1033	47	538	52	390	71	0	.	1085	52	3389	25	2274	28	5107	19	10759	13	5333	18	0	.	155	100	0	.	663	48	0	.	0	.	0	.	3	.	0	.	109	72	1352	40	603	47	0	.	526	67	357	59	144	.	119	71	0	.	0	.	0	.	0	.	0	.	652	48	420	58	273	68	0	.	0	.	0	.	1138	37	945	47	1694	30	229	63	1	.	0	.	842	40	423	57	834	52	525	57	732	67	1536	36	1132	48	1219	43	1345	47	0	.	0	.	186	82	0	.	0	.	0	.	0	.	41	.	242	61	0	.	0	.	0	.	0	.	5243	19	5634	18	5311	18	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	72829	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	18	61	0	.	0	.	28	68	72	49	157	44	614	24	756	17	463	35	695	18	44	100	35	62	102	46	0	.	10	78	101	30	305	33	127	49	0	.	170	27	142	39	125	31	20	64	166	35	0	.	532	17	268	37	178	47	438	22	61	60	184	27	25	58	114	40	206	30	166	37	98	62	165	34	146	45	69	41	363	32	115	47	217	25	69	60	159	40	151	41	83	55	64	39	217	32	110	35	134	49	45	90	0	.	31	84	0	.	87	67	0	.	195	35	149	36	96	42	337	32	231	38	137	35	157	42	131	48	16	90	100	39	52	53	137	44	8	237	0	.	228	30	8	.	48	62	180	27	66	48	166	51	53	53	29	63	39	62	21	61	64	80	0	.	21	80	272	26	58	43	63	43	28	85	210	32	128	50	0	.	0	.	4	.	0	.	12079	4
	21-30 cm	82	63	0	.	0	.	95	51	288	37	631	32	1269	19	1533	16	759	29	1625	16	25	77	44	64	266	37	0	.	68	53	336	38	881	28	184	52	0	.	375	38	431	32	304	39	13	71	258	38	0	.	893	20	293	32	352	33	719	23	107	71	401	29	134	53	181	41	513	35	508	40	35	139	427	32	428	30	223	41	585	34	383	50	603	24	205	49	212	37	211	37	110	57	289	38	423	36	456	35	192	44	199	39	0	.	92	68	0	.	203	64	0	.	293	42	355	36	143	47	727	33	435	35	225	44	354	39	107	50	92	71	116	42	83	48	448	39	174	67	0	.	376	35	15	.	92	71	455	23	199	42	269	42	74	51	124	59	83	92	47	89	37	116	0	.	0	.	583	25	245	37	94	45	37	75	358	38	292	48	0	.	12	.	20	.	0	.	25808	4
	31-40 cm	48	73	20	.	0	.	44	60	859	30	952	26	1620	17	1772	17	686	27	2225	16	0	0	124	56	271	40	0	.	233	68	302	36	1077	23	580	38	0	.	487	29	550	33	333	34	25	72	338	38	0	.	1706	19	475	29	568	36	1224	21	180	72	585	33	84	62	284	48	423	27	751	37	110	59	700	28	466	35	564	41	667	25	624	35	1160	22	398	36	524	43	558	35	80	50	310	45	367	31	640	35	408	32	414	47	0	.	31	73	0	.	460	94	0	.	164	40	371	32	279	43	328	41	282	38	226	38	406	43	100	93	9	100	330	38	82	44	383	46	336	50	0	.	860	25	123	.	66	71	617	25	230	34	354	44	67	75	120	58	95	69	184	64	27	100	0	.	0	0	721	27	327	35	185	47	103	56	704	28	360	32	0	.	0	.	12	.	0	.	35757	4
	41-50 cm	176	51	0	.	0	.	161	57	883	29	990	26	2308	20	2545	15	998	29	2439	15	48	100	63	85	295	45	0	.	222	59	572	32	942	26	797	37	0	.	1051	24	728	31	369	31	69	77	276	36	0	.	2199	18	516	32	677	28	1207	22	188	53	676	30	211	46	292	39	898	25	599	36	73	53	842	29	868	33	622	37	818	24	490	44	1427	24	388	40	363	39	395	35	157	65	474	35	470	38	613	29	682	33	357	38	0	.	66	67	0	.	477	65	0	.	120	44	147	33	118	60	321	35	335	42	274	40	194	39	95	72	222	71	356	45	249	50	322	42	213	50	16	.	777	26	47	.	165	55	700	23	248	36	528	31	214	45	199	62	87	60	129	64	44	100	0	.	0	.	680	28	439	38	317	40	147	71	673	28	720	31	0	.	0	.	18	.	0	.	42087	3
	51-60 cm	197	81	0	.	0	.	313	53	893	32	1342	30	2257	19	3275	15	967	27	1878	18	48	100	40	100	331	47	0	.	119	68	562	35	1000	25	637	38	0	.	1064	25	309	37	714	30	41	100	172	66	0	.	1576	21	488	33	785	33	1606	22	205	43	639	33	157	52	187	43	987	26	276	45	69	63	738	34	857	34	291	42	841	28	842	31	1451	21	199	48	371	45	82	51	350	60	476	34	577	30	881	32	635	32	338	50	0	.	72	74	0	.	484	79	0	.	88	54	122	50	20	100	172	41	215	42	267	51	202	55	78	72	53	71	159	65	157	54	269	42	312	43	0	.	527	26	107	.	58	73	429	27	412	39	333	38	320	48	28	100	297	54	162	59	77	75	0	.	0	.	539	38	400	39	286	51	245	70	534	35	576	37	0	.	0	.	69	.	0	.	40135	4
	61-70 cm	72	100	0	.	0	.	57	100	569	35	468	42	1359	25	1962	20	560	29	736	26	0	.	35	100	146	61	0	.	34	100	329	41	336	37	256	36	0	.	404	36	309	37	603	28	32	100	130	45	0	.	925	26	448	51	873	37	663	31	31	100	330	45	114	73	191	56	592	37	397	46	0	0	381	47	296	48	286	80	449	41	518	44	1830	24	123	62	121	76	28	100	0	0	183	52	285	48	272	57	302	56	232	52	0	.	84	71	0	.	107	71	0	.	107	65	114	73	61	100	216	42	0	.	97	72	93	58	98	58	71	71	150	74	216	66	257	48	165	51	0	.	519	54	21	.	102	58	234	39	339	45	175	52	244	55	91	75	130	51	0	.	118	72	0	.	0	.	306	36	82	100	159	62	0	.	714	36	200	48	0	.	0	.	29	.	0	.	23566	5
	71-80 cm	30	100	0	.	0	.	111	58	138	58	211	46	456	38	1165	24	306	49	425	32	0	.	51	100	164	74	0	.	0	.	208	55	363	47	87	71	0	.	293	51	109	71	324	46	81	100	120	60	0	.	510	41	185	71	279	44	414	39	171	50	181	50	0	.	140	74	308	38	78	71	39	100	413	56	434	45	123	78	311	49	481	48	602	35	0	.	91	100	35	100	0	.	0	.	359	39	131	58	281	77	46	100	0	.	40	100	0	.	63	100	0	.	0	.	45	100	30	100	0	.	47	100	105	63	41	100	143	80	140	100	72	71	256	46	86	71	75	71	0	.	33	100	0	.	38	100	89	71	181	62	46	100	0	.	0	.	89	100	0	.	110	74	0	.	0	.	90	58	89	71	51	100	0	.	537	37	133	100	0	.	0	.	42	.	0	.	12925	7
	81-90 cm	0	.	0	.	0	.	0	.	49	100	0	.	91	100	588	34	454	42	63	100	0	.	0	.	0	.	0	.	0	.	175	71	112	71	64	100	0	.	64	100	59	100	88	71	0	.	31	100	0	.	104	71	0	.	238	50	44	100	159	73	115	72	0	.	122	71	0	.	0	.	0	.	40	100	189	72	0	.	95	77	135	58	444	40	0	.	0	.	62	100	0	.	0	.	69	100	84	100	39	100	0	.	0	.	0	.	0	.	81	100	0	.	28	100	73	71	0	.	89	71	0	.	0	.	0	.	0	.	53	100	63	100	59	100	0	.	121	73	0	.	0	.	0	.	0	.	0	.	0	.	0	.	49	100	0	.	0	.	0	.	78	100	0	.	0	.	0	0	97	100	135	71	76	100	97	71	0	.	0	.	0	.	0	.	0	.	4875	11
	91-100 cm	0	.	0	.	0	.	54	100	0	.	0	.	66	100	176	58	0	.	55	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	102	80	0	.	0	.	0	.	123	71	0	.	68	100	0	.	0	.	0	.	65	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	114	100	0	.	75	100	58	100	0	.	0	.	0	.	0	.	0	.	0	.	68	100	0	.	55	100	52	100	0	.	0	.	0	.	89	100	0	.	0	.	0	0	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	63	100	0	.	0	.	0	.	0	.	0	.	0	.	81	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	21	100	0	.	60	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	1446	22
	>100 cm	0	.	0	.	0	.	0	.	0	.	0	.	0	.	133	100	72	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	185	71	58	100	0	.	0	.	0	.	70	100	0	.	0	.	0	0	0	.	0	.	0	.	0	.	50	100	0	.	0	.	61	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	68	100	0	.	0	.	0	.	0	.	111	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	.	808	33
	total	623	48	20	.	0	.	863	45	3751	28	4750	24	10042	15	13904	12	5264	20	10142	12	166	76	392	55	1576	37	0	.	687	54	2586	30	5016	19	2733	30	0	.	4009	21	2637	25	2859	24	279	67	1615	31	0	.	8698	15	2732	24	3949	25	6316	18	1167	39	3184	23	726	42	1510	35	3928	22	2775	29	424	46	3707	26	3798	26	2228	34	4203	21	3647	28	7795	17	1381	34	1840	31	1521	31	780	48	1796	30	2834	28	3187	25	2796	28	1682	35	0	.	415	50	0	.	2162	63	0	.	995	31	1376	30	747	38	2190	25	1545	30	1332	33	1447	36	751	49	656	58	1345	36	1217	42	1902	32	1405	44	16	.	3320	23	321	.	568	44	2784	21	1675	33	1871	29	1022	40	592	52	821	40	544	60	555	66	0	.	21	80	3213	23	1737	33	1349	37	637	63	3826	23	2408	29	0	.	12	.	192	.	0	.	199485	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	268	30	232	29	175	45	136	33	0	.	0	.	48	45	169	30	946	17	3	.	106	46	112	48	108	43	2	.	45	56	84	59	0	.	232	60	0	.	0	.	34	64	44	48	0	.	0	.	0	.	92	60	94	37	227	36	32	88	37	62	0	.	92	53	-2	.	0	.	0	.	0	.	121	100	-14	158	72	59	38	100	29	70	0	.	228	31	92	67	2	100	115	50	77	66	86	98	0	.	0	0	135	40	203	40	145	31	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	14	75	0	.	16	82	63	60	81	60	0	.	52	56	68	50	17	88	89	58	65	68	0	.	69	55	31	74	151	54	43	73	7	81	0	.	61	92	0	.	0	.	89	54	9	100	25	55	79	41	31	58	182	44	72	45	131	57	122	38	0	.	6211	6
	21-30 cm	303	27	314	33	320	35	407	36	0	.	0	.	62	63	286	44	1351	17	0	.	93	50	174	43	197	43	0	.	67	58	229	52	0	.	369	39	0	.	0	.	47	75	113	52	0	.	0	.	0	.	309	26	228	59	584	30	63	76	48	59	0	.	111	58	22	.	0	.	0	.	0	.	86	71	65	78	189	70	39	87	125	83	0	.	417	27	128	46	9	235	121	40	220	52	11	100	0	.	0	0	313	33	302	36	333	46	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	129	77	48	.	35	71	103	65	22	186	0	.	153	54	145	60	49	77	80	69	11	70	0	.	188	62	65	66	64	79	141	52	33	80	0	.	25	71	0	.	0	.	90	64	31	100	84	40	139	54	166	71	110	45	313	43	84	50	335	37	0	.	10699	6
	31-40 cm	396	31	502	31	243	45	467	35	0	.	0	.	243	48	495	34	1900	16	33	.	106	58	245	47	406	37	10	.	134	53	258	52	0	.	448	38	0	.	0	.	68	61	55	81	0	.	0	.	0	.	504	34	442	38	409	42	43	73	42	85	0	.	59	67	0	.	0	.	0	.	0	.	105	100	106	71	182	50	14	72	88	89	0	.	675	32	131	45	28	58	163	43	279	42	38	89	0	.	93	71	404	43	320	36	420	34	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	166	81	12	.	72	71	29	74	94	100	0	.	160	55	99	55	77	70	39	71	94	70	0	.	114	55	146	48	187	57	119	45	110	51	0	.	97	73	0	.	0	.	129	58	73	71	186	63	156	42	68	87	234	49	291	37	220	43	302	32	0	.	13825	5
	41-50 cm	718	31	286	35	502	33	610	28	0	.	0	.	443	47	378	32	2088	17	37	.	53	66	329	48	277	37	23	.	225	58	165	61	0	.	380	36	0	.	0	.	94	58	66	63	0	.	0	.	0	.	826	27	496	38	631	31	82	78	29	84	0	.	168	51	29	.	0	.	0	.	0	.	0	.	29	100	50	87	50	76	87	59	0	.	796	26	175	38	135	56	326	38	334	41	44	100	0	.	133	74	342	58	450	33	389	36	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	125	84	47	.	91	73	63	62	75	62	0	.	219	61	180	62	18	100	27	68	71	71	0	.	97	57	197	63	293	48	195	51	104	86	0	.	112	74	0	.	0	.	26	72	83	82	130	78	364	38	30	90	415	46	191	36	309	42	329	38	0	.	16066	5
	51-60 cm	394	31	429	29	270	43	871	26	0	.	0	.	206	55	444	37	2655	15	0	.	247	53	165	52	144	46	82	.	213	62	189	54	0	.	366	43	0	.	0	.	126	63	72	61	0	.	0	.	0	.	799	31	832	39	569	34	86	78	34	100	0	.	186	55	0	.	0	.	0	.	0	.	0	.	97	100	45	100	93	100	94	75	0	.	463	32	379	45	23	71	217	49	100	47	61	100	0	.	88	75	115	53	460	39	506	32	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	50	100	48	.	0	.	52	77	132	77	0	.	117	60	166	68	79	71	85	80	0	.	0	.	28	71	175	63	109	78	214	53	47	71	0	.	118	72	0	.	0	.	84	71	41	72	194	58	350	37	0	.	212	44	424	43	213	38	315	32	0	.	15376	6
	61-70 cm	261	49	282	40	195	53	431	36	0	.	0	.	120	73	233	44	1850	19	0	.	72	100	82	71	126	50	75	.	34	100	86	71	0	.	193	52	0	.	0	.	24	100	0	.	0	.	0	.	0	.	650	33	129	60	374	39	0	.	0	.	0	.	107	100	0	.	0	.	0	.	0	.	0	.	46	100	0	.	0	.	0	.	0	.	470	33	372	49	0	.	102	77	38	100	0	.	0	.	88	73	141	61	407	41	245	47	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	79	100	62	.	0	.	0	.	135	100	0	.	35	100	63	71	68	100	86	72	0	.	0	.	0	.	16	100	124	71	25	100	57	100	0	.	91	74	0	.	0	.	16	100	63	100	195	62	213	47	0	.	258	52	147	63	170	60	257	41	0	.	9395	7
	71-80 cm	136	59	75	71	200	45	631	33	0	.	0	.	0	.	265	46	708	28	0	.	42	100	90	100	84	71	0	.	34	100	59	73	0	.	38	100	0	.	0	.	33	100	0	.	0	.	0	.	0	.	84	71	205	60	151	60	0	.	37	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	45	100	0	.	314	43	331	47	0	.	89	100	24	100	38	100	0	.	0	.	25	100	88	100	165	76	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	38	100	0	.	97	71	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	59	72	0	.	0	.	0	.	0	.	18	100	0	.	124	59	64	100	0	.	0	.	107	71	129	60	0	.	0	.	4629	11
	81-90 cm	66	100	52	100	215	62	118	71	0	.	0	.	0	.	0	.	153	58	0	.	0	.	0	.	0	.	61	.	0	.	0	.	0	.	70	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	53	100	0	.	0	.	0	.	0	.	0	.	76	100	115	72	0	.	0	.	0	.	0	.	52	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	185	74	296	53	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	37	100	0	.	43	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	48	100	0	.	0	.	0	.	0	.	40	100	0	.	0	.	0	.	0	.	0	.	59	100	0	.	0	.	60	100	37	100	50	100	0	.	1885	19
	91-100 cm	0	.	54	100	0	.	63	100	0	.	0	.	0	.	0	.	98	71	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	52	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	181	73	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	109	71	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	55	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	45	100	0	.	0	.	0	.	657	31
	>100 cm	0	.	0	.	0	.	0	.	0	.	0	.	0	.	84	100	66	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	71	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	.	112	100	0	.	0	.	0	.	0	.	194	100	94	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	63	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	683	41
	total	2542	22	2225	22	2121	26	3734	22	0	.	0	.	1121	44	2354	26	11815	11	73	.	718	39	1197	38	1342	31	252	.	752	50	1071	47	0	.	2168	29	0	.	0	.	428	52	401	55	0	.	0	.	0	.	3265	24	2427	30	2945	24	307	74	227	44	0	.	775	49	49	.	0	.	0	.	0	.	312	70	404	67	653	56	235	72	467	63	0	.	3362	22	1840	34	197	57	1132	32	1184	36	278	75	0	.	401	72	1475	35	2610	26	2703	24	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	602	72	218	.	258	73	311	51	577	62	0	.	833	53	722	46	307	60	524	45	241	52	0	.	496	49	677	48	927	43	738	43	417	58	0	.	544	65	0	.	0	.	452	43	300	71	939	43	1424	29	295	68	1411	30	1650	30	1292	30	1710	27	0	.	79426	4
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	.	30	51	0	.	0	.	0	.	0	.	119	59	8	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	.	13	.	21	75	126	46	48	55	269	33	163	46	494	25	165	36	98	46	329	30	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	3	100	0	.	0	.	25	.	0	.	0	.	0	.	113	47	74	42	50	42	0	.	0	.	0	.	0	.	0	.	7	78	0	.	0	.	0	.	2156	10
	21-30 cm	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	95	75	0	.	0	.	0	.	0	.	236	46	45	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	.	35	.	26	100	248	47	110	60	213	44	260	37	958	24	245	41	236	49	534	30	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	48	78	0	.	0	.	35	.	0	.	0	.	0	.	165	36	108	57	54	55	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	3652	10
	31-40 cm	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	132	65	0	.	0	.	0	.	0	.	226	54	18	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	.	7	.	-1	100	132	48	73	63	164	39	307	37	657	24	98	46	218	41	397	34	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	62	71	0	.	0	.	12	.	0	.	0	.	0	.	140	43	91	55	40	71	0	.	0	.	0	.	0	.	0	.	21	100	0	.	0	.	0	.	2796	10
	41-50 cm	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	95	64	0	.	0	.	0	.	0	.	180	48	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	.	30	.	13	100	125	64	117	58	47	53	207	32	596	31	102	38	120	44	281	37	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	53	71	0	.	0	.	0	.	0	.	0	.	0	.	100	49	35	84	35	80	0	.	0	.	0	.	0	.	0	.	17	100	0	.	0	.	0	.	2181	12
	51-60 cm	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	52	100	0	.	0	.	0	.	0	.	61	71	40	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	.	0	.	6	100	40	73	0	.	35	73	136	44	318	47	73	53	87	61	187	41	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	136	80	20	100	0	.	0	.	0	.	0	.	0	.	0	.	38	71	0	.	0	.	0	.	1229	18
	61-70 cm	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	37	100	0	.	0	.	0	.	0	.	54	57	46	76	0	.	0	.	0	.	0	.	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	100	12	100	20	100	51	71	69	63	136	58	36	100	20	100	50	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	.	0	.	0	.	0	.	561	23
	71-80 cm	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	45	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	.	21	100	56	71	52	72	51	71	36	100	39	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	.	0	.	0	.	0	.	0	.	301	31
	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	.	45	100	28	100	0	.	0	.	27	100	27	100	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	.	153	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	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	54	100	0	.	0	.	0	.	56	100	0	.	0	.	35	100	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	.	0	.	0	.	0	.	0	.	0	.	0	.	174	52
	>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	.	37	100	0	.	0	.	0	.	0	.	198	100	0	.	175	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	.	0	.	0	.	0	.	0	.	0	.	0	.	411	55
	total	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	485	54	0	.	0	.	0	.	0	.	876	39	185	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	.	86	.	97	93	821	39	396	57	800	31	1196	31	3294	19	997	34	816	34	2055	25	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	165	71	0	.	0	.	71	.	0	.	0	.	0	.	655	38	328	51	209	37	0	.	0	.	0	.	0	.	0	.	83	77	0	.	0	.	0	.	13615	7
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	286	28	232	29	175	45	164	30	72	49	157	44	1409	13	926	15	1409	16	707	18	150	44	147	39	210	31	2	.	58	46	295	27	341	31	365	42	30	51	261	24	540	18	315	20	615	18	1307	14	1065	15	625	17	372	29	405	29	541	19	98	44	184	27	117	43	115	40	206	30	235	36	239	32	381	37	132	52	178	34	467	27	148	39	236	24	297	27	250	35	153	41	198	37	141	40	344	32	152	34	152	43	179	37	203	40	189	28	227	32	413	25	214	26	479	23	313	30	591	22	621	20	365	27	524	22	178	41	180	37	168	30	230	28	202	33	265	38	59	58	68	50	283	29	98	54	113	47	180	27	137	36	196	45	219	39	97	45	46	54	21	61	124	60	1148	17	834	15	925	15	66	39	88	34	107	37	242	29	309	33	78	42	131	57	126	37	0	.	28841	3
	21-30 cm	385	25	314	33	320	35	502	30	288	37	631	32	2599	12	1827	15	2110	15	1625	16	119	43	218	36	463	28	0	.	140	38	743	28	971	26	559	31	95	75	503	31	1061	19	1063	23	1219	18	2421	13	2006	13	1201	16	558	30	936	23	895	20	155	52	401	29	246	39	203	38	513	35	646	34	421	39	707	24	493	28	500	34	764	29	509	43	654	23	621	24	340	29	220	37	230	34	509	31	468	33	561	30	214	41	512	25	302	36	460	37	148	38	832	25	359	30	587	29	615	26	1101	22	1372	21	820	24	912	22	577	31	270	35	523	28	384	30	187	36	675	34	327	44	145	60	425	32	94	60	103	64	455	23	435	34	348	35	185	39	300	36	115	69	47	89	62	75	1736	14	1766	18	1864	16	277	34	178	30	176	45	524	34	402	37	313	43	96	45	355	36	0	.	56508	2
	31-40 cm	444	29	521	30	243	45	511	32	859	30	952	26	4203	10	2428	14	2585	13	2267	16	106	58	369	36	677	27	10	.	401	44	874	27	1161	22	1106	26	132	65	750	29	1645	17	1221	20	1324	20	3101	13	2969	13	2210	16	966	23	977	27	1371	19	222	60	585	33	143	46	284	48	423	27	861	34	492	30	1193	24	571	32	831	30	1029	24	743	31	1180	21	1073	24	655	36	585	34	243	33	589	31	539	25	763	31	539	28	818	32	320	36	459	32	232	43	1031	44	487	33	495	26	677	24	937	20	853	22	581	24	778	23	658	34	411	44	471	32	593	27	353	36	548	36	496	38	99	55	954	24	162	78	160	50	617	25	405	27	508	33	307	41	251	35	206	42	184	64	124	61	2186	16	1800	17	2355	15	400	31	372	39	259	34	772	27	594	27	312	35	220	43	314	31	0	.	74688	2
	41-50 cm	894	27	286	35	502	33	771	25	883	29	990	26	5550	12	3127	14	3086	15	2477	14	101	59	392	42	572	29	23	.	515	38	1033	25	1081	24	1251	26	95	64	1455	22	2504	17	1178	19	1500	20	3518	12	3724	12	3025	15	1026	24	1308	21	1420	19	216	47	676	30	379	34	320	37	898	25	699	32	345	31	1155	25	898	32	812	32	1053	20	661	36	1427	24	1183	22	538	29	529	29	484	33	808	26	794	29	677	28	903	28	698	34	450	33	484	30	240	40	1076	32	667	28	209	31	354	23	713	28	698	21	566	28	707	24	442	36	525	52	645	34	686	36	859	34	541	32	432	39	196	58	795	26	75	68	236	44	700	23	398	28	726	28	563	31	394	40	191	54	129	64	156	60	2266	17	1861	16	2278	15	521	34	447	36	511	34	703	27	1136	26	209	34	309	42	346	36	0	.	85882	2
	51-60 cm	592	34	429	29	270	43	1184	24	893	32	1342	30	4958	12	3816	14	3622	13	1889	18	295	47	205	46	476	35	82	.	443	43	887	26	1121	23	1118	27	52	100	1233	22	2029	17	1196	22	1798	21	2935	14	2724	13	2375	17	1366	27	1354	24	1930	20	238	40	639	33	343	38	187	43	987	26	304	42	314	42	896	29	953	32	449	32	1055	25	936	29	1493	21	663	26	750	32	106	43	566	41	576	29	828	25	967	30	803	28	453	40	460	39	579	30	322	35	1004	41	530	35	201	35	258	33	337	45	527	27	409	30	554	30	406	39	288	38	351	40	512	38	493	31	520	33	429	35	166	68	606	25	191	66	58	73	429	27	440	36	526	32	513	35	243	48	345	48	162	59	196	53	2011	16	1556	19	2195	18	441	36	479	39	595	36	534	35	787	29	462	40	213	38	385	32	0	.	78837	2
	61-70 cm	334	44	282	40	195	53	488	34	569	35	468	42	3083	15	2279	18	2410	16	736	26	72	100	117	58	272	40	75	.	103	58	415	36	382	35	475	29	37	100	665	30	1086	21	913	23	1118	26	1851	17	1549	22	1576	20	577	42	1246	28	663	31	31	100	330	45	221	61	191	56	592	37	466	41	39	71	500	39	342	44	396	63	508	37	544	42	1858	23	593	29	493	42	28	100	102	77	221	46	534	35	272	57	416	44	373	40	407	41	328	39	224	36	365	34	318	35	181	45	182	51	197	51	367	31	66	58	269	46	261	44	295	40	162	52	351	50	573	40	658	41	201	45	63	71	664	45	107	61	102	58	234	39	339	45	190	49	403	40	116	62	187	47	0	.	210	52	1131	24	829	24	1348	21	145	71	354	44	213	47	714	36	457	36	147	63	170	60	286	38	0	.	46901	3
	71-80 cm	165	52	75	71	200	45	742	29	138	58	211	46	1590	19	1430	22	1014	24	425	32	42	100	141	73	249	55	0	.	34	100	267	46	392	44	209	53	45	100	629	38	701	28	417	39	779	28	825	23	599	26	595	37	390	46	430	35	442	37	209	45	181	50	0	.	140	74	308	38	127	52	131	50	522	47	434	45	157	65	411	41	525	45	639	34	314	43	422	42	35	100	89	100	24	100	442	34	131	58	281	77	71	74	88	100	206	64	256	65	294	62	192	50	46	71	101	59	82	59	183	41	168	46	210	46	70	72	143	80	266	63	198	46	482	31	118	59	173	51	0	.	87	73	0	.	38	100	89	71	181	62	46	100	28	100	0	.	148	67	0	.	110	74	976	30	290	42	852	26	89	71	175	51	64	100	537	37	133	100	107	71	129	60	42	100	0	.	26166	5
	81-90 cm	66	100	52	100	215	62	118	71	49	100	0	.	281	47	588	34	607	35	186	74	0	.	0	.	0	.	61	.	0	.	175	71	199	59	135	71	0	.	210	47	471	43	213	45	231	47	632	37	374	44	104	71	0	.	238	50	44	100	159	73	115	72	53	100	122	71	0	.	0	.	105	100	40	100	264	59	115	72	163	54	135	58	444	40	0	.	52	100	62	100	0	.	0	.	112	72	84	100	39	100	0	.	185	74	296	53	79	100	180	60	93	76	28	100	73	71	27	100	184	46	28	100	116	59	60	73	0	.	96	71	92	75	59	100	0	.	121	73	0	.	0	.	0	.	0	.	0	.	0	.	48	100	49	100	0	.	0	.	0	.	117	74	642	32	88	59	69	71	97	100	135	71	135	71	97	71	0	.	60	100	37	100	50	100	0	.	10652	8
	91-100 cm	0	.	54	100	0	.	117	71	0	.	0	.	237	50	176	58	98	71	127	71	0	.	0	.	0	.	0	.	0	.	0	.	72	100	0	.	0	.	257	47	96	72	182	58	114	71	308	45	48	100	68	100	0	.	0	.	0	.	65	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	114	100	0	.	130	72	58	100	0	.	0	.	181	73	0	.	0	.	0	.	68	100	0	.	55	100	52	100	0	.	109	71	0	.	143	73	0	.	38	100	0	0	56	100	77	100	0	.	35	100	0	.	0	.	0	.	0	.	111	71	57	100	0	.	0	.	0	.	55	100	0	.	81	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	225	45	136	58	78	58	0	.	60	100	0	.	0	.	0	.	45	100	0	.	0	.	0	.	3980	12
	>100 cm	0	.	0	.	0	.	0	.	0	.	0	.	36	100	217	73	138	71	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	71	100	0	.	51	100	0	.	0	.	155	71	315	46	52	100	185	71	58	100	0	.	0	.	0	.	70	100	0	.	0	.	0	0	0	.	0	.	0	.	0	.	50	100	38	100	0	.	61	100	0	.	0	.	0	.	0	.	112	100	0	.	0	.	68	100	0	.	194	100	94	100	129	100	148	79	0	.	0	.	0	.	0	.	198	100	0	.	175	59	0	.	0	.	0	.	0	.	49	100	0	.	0	.	0	.	0	.	63	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	39	100	0	.	64	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	2830	18
	total	3166	20	2245	22	2121	26	4596	20	3751	28	4750	24	23946	9	16814	10	17079	10	10439	12	884	34	1589	32	2918	24	252	.	1694	35	4690	22	5719	17	5291	20	485	54	6015	18	10133	13	6697	16	8852	15	17213	9	15112	10	11963	12	5313	19	6895	17	7305	16	1393	33	3184	23	1501	32	1562	34	3928	22	3339	26	2086	29	5392	21	4202	25	3489	26	5619	18	4259	25	7990	17	4744	18	3681	23	1717	28	1913	27	2980	23	4130	22	3607	23	3470	24	3157	24	2610	26	3204	21	1857	28	5487	28	2859	22	2264	20	2573	21	4041	17	5080	15	3004	19	4280	19	2654	28	2111	34	2682	26	3047	25	3368	25	3382	26	2238	34	738	45	3813	21	845	47	809	34	2784	21	2336	27	2589	24	2267	26	1401	32	1238	33	544	60	1098	46	12360	12	9160	13	12028	12	2036	30	2287	28	2060	28	4122	22	3819	21	1733	29	1304	30	1903	26	0	.	415285	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. 2282143. Birmensdorf, Swiss Federal Research Institute WSL

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