Selection from the list of topics

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

1. What do the numbers stand for?

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

Example 1: Estimated value and standard error

NFI5

volume of deadwood (stemwood)
ownership (2 categories)

regional demarcation: production region

unit: m³/ha

evaluation area: accessible forest without shrub forest

grid: 1.4 km grid, subgrids 1-5

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

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

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2. What is the purpose of the standard error?

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

The statistical certainty is:

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

Example 2: Calculating confidence intervals

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

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

Procedure

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

Answer

			Step 1	Step 2

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

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

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

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

Data: see example 2

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

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

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3. When are two results statistically different?*

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

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

Example 4: Interpretation of two results from the same inventory

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

	case 2						case 1

case 1

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

Procedure

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

Answer

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

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

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

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

Case 2

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

Procedure

See case 1.

Answer

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

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

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

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

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

Example 5: Interpretation of two results from different inventories

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

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

Procedure

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

Answer

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

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

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

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

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

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

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

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

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

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

Procedure

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

Answer

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

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

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

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

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

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

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

Procedure

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

Answer

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

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

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

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

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

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

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

Example 8: Standard error and combination of variable expressions

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

The standard error increases as the level of detail increases.

Large standard errors are to be expected if:

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

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

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

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5. Two types of changes?

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

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

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

The results are:

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

Example 9: : Additivity/non-additivity of changes

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

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

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

Example 10: Average number of years per domain

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

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

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

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

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

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

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

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

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

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

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NFI4
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 NFI4/NFI5
grid: 1.4 km grid, subgrids 1-5
state 2009/17
		forest district (2024)
		AG01		AG02		AG03		AG04		AI01		AR01		BE01		BE02		BE03		BE04		BSBL01		BSBL02		BSBL03		BSBL04		FR01		FR02		FR03		FR04		GE01		GL01		GR01		GR02		GR03		GR04		GR05		JU01		LU01		LU02		LU03		NE01		NE02		NE03		NE04		NE06		NW01		OW01		OW02		SG01		SG02		SG03		SG04		SG05		SH01		SO01		SO02		SO03		SO04		SZ01		SZ02		SZ03		TG01		TG02		TG03		TI01		TI02		TI03		TI04		TI05		TI06		TI07		TI08		TI09		UR01		UR02		UR03		VD02		VD03		VD04		VD05		VD06		VD07		VD08		VD09		VD11		VD12		VD14		VD15		VD16		VD18		VD20		VD22		VS01		VS02		VS03		ZG01		ZH01		ZH02		ZH03		ZH04		ZH05		ZH06		ZH07		lakes		Switzerland
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	.	18	72	0	.	3	75	45	31	327	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	.	21	69	10	90	28	98	0	.	0	.	3	166	9	.	3	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	98	51	63	42	9	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	637	15
	21-30 cm	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	18	72	0	.	7	100	86	45	520	22	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	46	71	49	67	-4	100	0	.	0	.	8	100	3	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	309	40	63	43	21	84	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	1127	16
	31-40 cm	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	33	83	0	.	15	100	151	37	751	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	.	2	715	46	63	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	198	31	238	48	36	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	1470	15
	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	.	0	.	175	34	647	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	76	15	72	0	.	0	.	0	.	0	.	0	.	20	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	359	32	101	48	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	1380	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	.	0	.	151	48	581	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	.	11	.	14	100	15	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	163	45	72	52	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	1006	22
	61-70 cm	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	53	100	0	.	0	.	0	0	227	36	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	18	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	50	71	72	64	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	421	27
	71-80 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	.	51	72	168	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	.	26	.	0	.	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	.	150	38	26	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	473	25
	81-90 cm	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	72	72	148	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	.	0	.	0	.	61	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	.	23	100	19	100	25	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	348	37
	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	.	61	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	.	28	100	0	0	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	89	75
	>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	.	35	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	.	38	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	125	59
	total	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	179	80	0	.	25	93	765	30	3481	19	0	.	0	.	0	.	0	.	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	.	120	52	177	53	85	78	0	.	0	.	11	64	13	.	22	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	1416	26	655	35	91	76	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	7075	12
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	.	205	28	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	31	.	0	.	0	.	24	74	158	31	26	38	128	34	225	38	380	29	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	56	100	45	69	65	72	0	.	0	.	42	65	0	.	12	.	0	.	0	.	0	.	0	.	0	.	13	72	0	.	0	.	0	.	0	.	0	.	10	63	86	50	26	51	0	.	0	.	0	.	75	39	8	80	5	.	0	.	7	72	54	69	5	100	11	65	3	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	8	.	0	.	0	.	0	.	0	.	246	25	189	38	77	45	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	2220	10
	21-30 cm	0	.	0	.	0	.	0	.	0	.	0	.	632	22	7	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	47	.	0	.	0	.	44	77	237	39	147	52	300	33	414	34	748	23	0	.	0	.	0	.	7	.	0	.	0	.	0	.	0	.	0	.	93	84	65	100	106	65	0	.	0	.	32	68	0	.	15	.	0	.	0	.	0	.	0	.	0	.	7	100	0	.	0	.	0	.	0	.	0	.	0	.	205	44	54	69	30	100	0	.	0	.	193	43	12	72	0	.	16	.	30	77	46	67	35	72	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	8	.	0	.	0	.	0	.	0	.	405	32	401	31	231	32	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	4567	9
	31-40 cm	0	.	0	.	0	.	0	.	0	.	0	.	1131	21	35	81	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	51	.	0	.	0	.	-13	233	587	29	229	45	522	35	593	31	942	23	0	.	0	.	0	.	20	.	0	.	0	.	0	.	0	.	0	.	83	82	83	68	75	65	0	.	0	.	232	65	0	.	20	.	0	.	0	.	0	.	0	.	0	.	33	76	0	.	0	.	0	.	0	.	0	.	75	69	304	39	81	49	9	100	0	.	0	.	64	56	17	59	0	.	0	.	108	78	38	73	53	72	63	72	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	35	.	0	.	0	.	0	.	0	.	631	29	503	30	497	34	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	7101	8
	41-50 cm	0	.	0	.	0	.	0	.	0	.	0	.	1360	23	61	71	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	103	58	634	26	281	42	877	33	601	31	1330	20	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	59	60	43	59	82	74	0	.	31	.	152	65	0	.	0	.	0	.	0	.	0	.	0	.	0	.	74	100	0	.	0	.	0	.	0	.	0	.	64	73	200	42	117	60	0	.	0	.	0	.	102	49	33	73	0	.	0	.	60	99	33	78	0	.	66	59	36	70	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	31	.	0	.	0	.	0	.	0	.	748	34	541	30	432	34	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	8153	8
	51-60 cm	0	.	0	.	0	.	0	.	0	.	0	.	792	24	48	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	124	66	734	28	152	55	650	26	460	32	1110	22	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	86	78	11	100	31	100	0	.	24	.	67	62	0	.	0	.	0	.	0	.	0	.	0	.	0	.	52	75	0	.	0	.	0	.	0	.	0	.	195	52	354	40	58	71	0	.	0	.	0	.	181	53	7	100	0	.	39	.	81	71	16	100	18	100	75	60	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	34	.	0	.	0	.	0	.	0	.	784	27	572	35	706	33	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	7463	8
	61-70 cm	0	.	0	.	0	.	0	.	0	.	0	.	405	40	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	52	71	344	43	64	61	395	41	215	37	537	32	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	19	100	26	100	25	100	0	.	0	.	26	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	88	77	0	.	0	.	0	.	0	.	0	.	42	72	131	61	51	59	0	.	0	.	0	.	55	100	24	100	0	.	0	.	45	71	0	.	42	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	13	.	0	.	0	.	0	.	0	.	642	37	158	42	206	51	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	3605	12
	71-80 cm	0	.	0	.	0	.	0	.	0	.	0	.	337	41	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	46	100	510	44	35	100	94	58	46	71	146	60	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	25	100	0	.	0	.	0	.	26	.	26	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	92	100	0	.	0	.	0	.	0	.	0	.	140	62	33	100	0	.	0	.	0	.	0	.	100	60	24	100	0	.	23	.	0	.	0	.	0	.	83	58	30	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	515	38	30	100	214	54	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	2575	16
	81-90 cm	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	53	71	65	100	39	100	234	48	66	71	85	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	.	0	.	0	0	0	.	0	.	0	.	0	.	30	100	0	.	0	.	0	.	0	.	0	.	70	100	0	.	49	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	262	45	34	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	988	22
	91-100 cm	0	.	0	.	0	.	0	.	0	.	0	.	34	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	36	100	92	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	.	64	100	0	0	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	226	54
	>100 cm	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	127	71	72	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	36	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	.	236	51
	total	0	.	0	.	0	.	0	.	0	.	0	.	4896	20	151	75	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	129	.	0	.	0	.	469	53	3361	24	973	36	3328	24	2693	24	5278	17	0	.	0	.	0	.	27	.	0	.	0	.	0	.	0	.	0	.	420	62	274	67	385	51	0	.	81	.	614	54	0	.	48	.	0	.	0	.	0	.	0	.	0	.	358	69	0	.	0	.	0	.	0	.	0	.	527	49	1313	32	387	49	39	100	0	.	0	.	801	35	125	64	5	.	78	.	331	74	187	70	223	71	298	49	119	84	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	130	.	0	.	0	.	0	.	0	.	4296	22	2427	25	2362	27	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	37132	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	.	472	20	2	100	0	.	4	100	0	.	0	.	0	.	0	.	7	.	70	46	4	100	4	71	0	.	27	82	103	41	150	32	543	24	632	18	414	23	0	.	16	100	0	.	89	51	0	.	0	.	0	.	0	.	0	.	6	80	103	51	10	56	0	.	22	82	27	57	4	.	6	100	0	.	0	.	0	.	0	.	0	.	22	50	69	69	21	60	0	.	0	.	0	.	181	43	66	60	64	39	8	73	0	.	0	.	45	38	20	62	41	86	30	67	31	60	114	44	47	74	58	48	83	60	0	.	0	.	2	100	0	.	0	.	0	.	0	.	0	.	11	81	0	.	0	.	0	.	0	.	503	23	634	24	420	29	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	5184	6
	21-30 cm	0	.	0	.	0	.	0	.	0	.	0	.	816	21	0	8772	0	.	0	.	0	.	0	.	0	.	0	.	0	.	259	59	21	70	23	78	0	.	115	72	157	46	362	37	597	23	1117	20	739	21	0	.	36	88	0	.	118	49	0	.	0	.	0	.	0	.	0	.	54	84	348	41	70	50	0	.	52	72	34	68	15	.	0	0	0	.	0	.	0	.	0	.	0	.	16	74	55	108	17	75	0	.	0	.	0	.	126	53	108	57	176	35	21	58	0	.	0	.	123	45	74	58	100	59	41	104	97	75	271	40	67	55	25	77	227	96	0	.	0	.	0	.	0	.	0	.	0	.	0	.	12	.	37	100	0	.	0	.	0	.	0	.	821	21	1082	24	787	28	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	9216	7
	31-40 cm	0	.	0	.	0	.	0	.	0	.	0	.	1214	21	153	68	0	.	10	100	0	.	0	.	0	.	0	.	25	.	284	50	52	61	69	72	0	.	7	100	568	32	390	33	630	26	1949	18	1441	24	0	.	32	100	0	.	144	52	0	.	0	.	0	.	0	.	0	.	43	100	237	48	125	58	0	.	116	75	36	63	42	.	0	.	0	.	0	.	0	.	0	.	0	.	121	52	78	105	45	76	0	.	0	.	0	.	150	54	70	66	339	50	71	57	0	.	0	.	210	45	71	66	141	68	73	74	164	72	373	48	114	52	248	61	95	54	0	.	0	.	0	.	0	.	0	.	0	.	0	.	21	.	77	89	0	.	0	.	0	.	0	.	1136	21	856	22	763	26	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	12786	6
	41-50 cm	0	.	0	.	0	.	0	.	0	.	0	.	1588	21	160	54	0	.	0	.	0	.	0	.	0	.	0	.	83	.	183	56	103	73	98	71	0	.	164	64	1005	30	289	38	794	27	2073	16	1346	22	0	.	38	100	0	.	144	57	0	.	0	.	0	.	0	.	0	.	9	100	215	47	135	56	0	.	126	71	0	0	68	.	132	71	0	.	0	.	0	.	0	.	0	.	213	56	95	85	59	85	0	.	0	.	0	.	63	51	72	54	699	38	36	73	0	.	0	.	76	56	61	69	53	77	178	63	206	81	370	47	219	87	316	48	139	77	0	.	0	.	0	0	0	.	0	.	0	.	0	.	1	.	94	59	0	.	0	.	0	.	0	.	854	25	1031	24	911	25	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	14502	6
	51-60 cm	0	.	0	.	0	.	0	.	0	.	0	.	1870	24	58	78	0	.	10	100	0	.	0	.	0	.	0	.	54	.	98	61	154	73	52	73	0	.	103	63	722	31	283	42	1124	30	2129	20	855	30	0	.	-5	100	0	.	137	55	0	.	0	.	0	.	0	.	0	.	0	.	172	68	107	51	0	.	37	100	0	0	19	.	216	72	0	.	0	.	0	.	0	.	0	.	109	59	65	100	69	100	0	.	0	.	0	.	107	55	102	64	414	43	49	75	0	.	0	.	66	62	82	71	85	73	94	79	37	100	224	45	290	56	203	58	182	51	0	.	0	.	0	.	0	.	0	.	0	.	0	.	27	.	38	72	0	.	0	.	0	.	0	.	713	25	752	26	1007	25	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	12910	7
	61-70 cm	0	.	0	.	0	.	0	.	0	.	0	.	886	26	41	100	0	.	0	.	0	.	0	.	0	.	0	.	35	.	0	.	53	100	71	74	0	.	147	84	296	41	131	57	602	28	1128	20	243	47	0	.	0	.	0	.	23	100	0	.	0	.	0	.	0	.	0	.	0	.	101	65	43	72	0	.	31	100	47	71	12	.	34	100	0	.	0	.	0	.	0	.	0	.	127	67	0	.	23	100	0	.	0	.	0	.	154	85	153	53	306	44	20	100	0	.	0	.	19	100	29	100	195	85	39	100	62	100	92	75	71	83	110	71	329	68	0	.	0	.	75	100	0	.	0	.	0	.	0	.	23	.	27	100	0	.	0	.	0	.	0	.	294	62	409	34	480	39	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	6961	9
	71-80 cm	0	.	0	.	0	.	0	.	0	.	0	.	547	30	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	58	100	20	100	0	.	286	62	219	41	92	73	306	40	586	35	152	46	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	113	81	115	72	0	.	0	.	29	100	0	.	76	100	0	.	0	.	0	.	0	.	0	.	38	100	0	.	0	.	0	.	0	.	0	.	136	60	125	78	163	55	29	100	0	.	0	.	0	0	53	71	56	100	64	71	0	.	39	100	23	100	0	0	0	.	0	.	0	.	46	100	0	.	0	.	0	.	0	.	0	.	30	100	0	.	0	.	0	.	0	.	371	46	98	59	337	42	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	4207	12
	81-90 cm	0	.	0	.	0	.	0	.	0	.	0	.	387	48	0	.	0	.	106	100	0	.	0	.	0	.	0	.	0	.	0	.	39	100	0	.	0	.	34	100	46	100	135	72	136	59	473	36	71	79	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	44	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	53	100	119	71	0	0	0	.	0	.	0	.	0	.	41	100	0	.	0	.	0	.	33	100	52	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	173	76	137	61	36	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	2115	18
	91-100 cm	0	.	0	.	0	.	0	.	0	.	0	.	44	100	0	.	0	.	65	100	0	.	0	.	0	.	0	.	0	.	0	.	48	100	0	.	0	.	108	71	0	.	0	.	61	100	47	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	.	37	100	0	.	0	.	0	.	0	.	0	.	75	100	0	.	0	.	0	.	47	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	51	100	94	71	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	676	28
	>100 cm	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	51	100	0	.	0	.	0	.	211	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	.	163	100	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	.	53	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	515	43
	total	0	.	0	.	0	.	0	.	0	.	0	.	7823	17	414	57	0	.	196	93	0	.	0	.	0	.	0	.	203	.	894	49	531	59	337	71	0	.	1041	53	3115	25	1832	29	4794	20	10345	13	5261	18	0	.	116	96	0	.	655	42	0	.	0	.	0	.	0	.	0	.	111	72	1289	40	606	48	0	.	385	71	217	63	160	.	465	71	0	.	0	.	0	.	0	.	0	.	647	46	363	71	234	72	0	.	0	.	0	.	1116	36	748	51	2281	30	234	58	0	.	0	.	615	41	389	55	713	57	520	64	645	65	1483	39	865	54	1050	44	1056	53	0	.	0	.	123	98	0	.	0	.	0	.	0	.	84	.	314	60	0	.	0	.	0	.	0	.	4917	18	5092	18	4795	19	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	69071	5
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	17	100	0	.	0	.	35	65	48	62	207	36	613	21	568	17	363	31	723	18	0	.	23	58	141	35	0	.	29	68	123	35	404	24	93	46	0	.	197	33	133	50	152	33	12	126	136	38	0	.	551	19	230	35	154	28	421	20	75	59	238	31	39	47	104	36	174	35	158	37	62	49	148	35	153	39	67	51	288	29	175	41	158	29	80	44	133	39	142	46	62	56	71	41	253	32	174	45	120	52	141	40	0	.	27	60	0	.	34	53	0	.	182	35	176	37	96	38	344	29	252	39	131	41	157	41	150	55	33	70	119	42	46	51	192	40	100	63	9	.	259	28	7	.	36	65	241	26	89	61	164	41	40	51	79	70	85	57	8	100	10	74	0	.	17	80	310	32	73	40	92	60	-26	154	156	29	107	70	0	.	6	.	10	.	0	.	12197	4
	21-30 cm	90	63	14	.	0	.	95	51	340	38	604	27	1113	19	1464	17	594	28	2012	17	13	100	79	55	263	37	0	.	177	62	333	41	891	28	279	51	0	.	727	31	445	35	204	39	12	71	308	34	0	.	826	19	282	33	341	32	862	22	187	65	346	27	76	63	142	40	387	34	462	34	41	77	568	32	275	39	316	41	571	30	349	43	625	23	300	47	185	41	253	40	75	65	231	44	378	36	421	32	350	40	282	42	0	.	134	81	0	.	114	59	0	.	294	39	466	41	149	49	565	35	434	35	221	44	374	41	89	63	25	63	133	44	95	50	261	43	195	66	0	.	527	29	29	.	52	71	508	28	201	46	355	41	58	49	219	56	118	71	37	98	49	100	0	.	0	0	566	26	282	36	163	49	20	71	543	33	333	38	0	.	30	.	8	.	0	.	26831	4
	31-40 cm	98	48	0	.	0	.	72	63	764	30	1199	25	1835	18	2114	15	805	30	2631	15	23	100	99	65	252	55	0	.	233	58	481	34	869	26	427	36	0	.	888	29	401	30	421	31	39	86	237	41	0	.	1927	18	549	34	650	35	1242	24	196	51	641	34	130	58	314	40	552	24	732	33	97	50	691	30	488	34	551	37	832	24	524	34	1206	23	448	37	383	48	564	34	78	58	253	41	367	32	637	27	491	37	466	37	0	.	126	61	0	.	96	60	0	.	94	54	264	32	161	53	249	36	169	43	244	39	297	40	67	91	55	64	257	47	99	52	371	41	268	51	0	.	744	27	100	.	94	59	650	24	249	34	413	36	138	60	176	66	91	69	234	55	28	100	0	.	0	.	684	26	256	47	355	42	55	62	661	28	559	32	0	.	90	.	12	.	0	.	37304	3
	41-50 cm	163	55	14	.	0	.	274	46	899	28	1464	26	2221	19	2492	14	1160	26	2865	15	92	100	38	100	383	46	0	.	134	71	592	34	986	30	593	36	0	.	1389	23	599	33	553	28	43	71	159	44	0	.	2259	18	514	31	821	29	1898	21	205	49	680	31	202	49	320	41	970	25	425	36	42	63	819	29	755	31	573	40	636	28	421	47	1586	22	334	44	292	36	523	36	133	59	546	30	583	32	617	29	585	34	364	38	0	.	109	54	0	.	164	48	0	.	97	56	167	43	63	52	278	38	195	41	176	50	124	47	106	59	207	71	334	46	98	55	338	40	194	58	58	.	662	26	7	.	130	53	721	24	210	46	581	32	255	44	173	74	262	54	153	69	22	124	0	.	0	.	665	30	365	45	250	47	166	60	807	25	720	31	0	.	108	.	18	.	0	.	43201	3
	51-60 cm	218	61	0	.	0	.	264	49	767	32	1309	29	2245	19	3201	15	1182	25	1880	19	20	100	19	100	494	41	0	.	44	71	459	36	857	28	487	38	0	.	1023	26	216	52	639	30	56	75	164	64	0	.	1456	18	492	34	850	30	1571	25	122	59	580	41	152	69	263	41	789	27	392	45	54	74	767	34	679	37	158	48	706	32	909	34	1479	22	201	62	404	43	153	58	335	60	298	39	427	34	774	31	557	35	403	47	0	.	67	71	0	.	294	53	0	.	90	53	65	81	31	72	104	55	154	50	142	52	181	55	80	75	102	86	156	54	192	72	470	56	210	53	22	.	466	29	77	.	178	54	365	28	537	36	355	46	401	56	143	72	110	59	260	52	130	73	0	.	0	.	454	37	291	42	246	57	72	71	836	32	405	42	0	.	0	.	89	.	0	.	38290	4
	61-70 cm	65	100	0	.	0	.	95	58	395	40	728	37	1133	29	1872	20	585	34	585	30	0	.	34	100	255	55	0	.	28	100	373	42	699	41	204	53	0	.	365	34	164	45	569	30	25	100	56	100	0	.	699	29	584	45	682	36	766	30	179	51	199	46	134	71	113	74	684	29	191	45	0	.	455	41	296	38	169	62	502	42	256	53	1240	30	30	100	150	65	108	58	83	72	108	59	462	43	229	48	279	47	54	71	0	.	91	73	0	.	0	.	0	.	85	75	91	58	82	100	189	47	0	.	98	59	152	52	73	72	72	71	169	52	240	51	175	57	128	50	0	.	439	54	20	.	146	78	220	36	260	54	30	100	117	60	0	.	193	53	0	.	25	100	0	.	0	.	210	39	132	75	407	57	33	100	521	34	150	61	0	.	0	.	31	.	0	.	21461	5
	71-80 cm	0	.	0	.	0	.	0	.	149	75	130	74	170	50	1348	22	611	36	237	41	0	.	44	100	112	100	0	.	0	.	143	65	211	62	118	76	0	.	214	51	94	74	223	44	75	100	106	62	0	.	455	35	234	67	312	49	405	48	129	74	84	71	0	.	197	59	97	71	0	.	34	100	218	51	289	57	81	72	337	53	541	44	705	35	0	.	69	100	0	.	63	100	0	.	335	51	51	100	211	84	39	100	0	.	42	100	0	.	57	100	0	.	0	.	36	100	0	.	72	74	0	.	47	71	82	71	92	100	95	100	82	73	69	71	32	100	36	100	0	.	42	100	0	.	53	100	90	72	83	100	44	100	107	72	0	.	0	.	111	100	163	79	0	.	0	.	47	71	100	77	93	71	51	100	82	71	40	100	0	.	0	.	0	.	0	.	10719	8
	81-90 cm	0	.	0	.	0	.	63	100	0	.	0	.	188	59	619	34	282	50	69	100	0	.	0	.	0	.	0	.	0	.	71	100	53	100	0	.	0	.	139	61	44	100	70	73	0	.	79	73	0	.	99	72	0	.	0	.	42	100	56	100	62	100	0	.	0	.	0	.	0	.	0	.	0	.	79	100	0	.	0	.	118	71	371	80	0	.	0	.	52	100	0	.	0	.	66	100	53	100	92	74	56	100	0	.	0	.	0	.	74	100	0	.	26	100	29	100	0	.	0	.	0	.	0	.	0	.	0	.	46	100	67	100	103	100	0	.	102	73	0	.	0	.	0	.	0	.	67	100	0	.	0	.	72	100	0	.	0	.	81	100	0	.	0	.	0	.	64	72	0	.	113	72	0	.	47	100	0	.	0	.	0	.	0	.	0	.	3712	15
	91-100 cm	0	.	0	.	0	.	54	100	0	.	0	.	0	.	0	.	89	100	0	0	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	0	0	.	0	.	0	.	69	100	0	.	69	100	53	100	0	.	0	.	0	.	84	100	72	100	0	.	0	.	0	.	0	.	0	.	0	.	55	100	0	.	0	0	81	100	0	.	0	.	0	.	0	.	0	.	65	100	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	.	60	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	46	100	0	.	0	.	0	.	0	.	0	.	0	.	838	28
	>100 cm	0	.	67	.	0	.	0	.	0	.	0	.	0	.	126	100	68	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	67	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	0	0	.	62	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	43	100	0	.	0	.	0	.	0	.	117	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	.	551	40
	total	651	47	96	.	0	.	952	42	3362	28	5641	22	9519	15	13804	12	5738	20	11002	12	148	100	337	53	1900	36	0	.	644	55	2575	30	4969	20	2200	31	0	.	4942	21	2096	25	2830	24	261	66	1314	33	0	.	8409	15	2937	26	3809	25	7207	19	1149	40	2915	24	804	43	1453	34	3653	22	2358	29	329	53	3665	25	3014	27	1969	33	3870	23	3292	28	7513	18	1394	35	1616	31	1796	28	829	45	1507	31	2935	26	2956	25	2771	27	1804	34	0	.	595	57	0	.	950	47	0	.	867	33	1293	32	580	40	1803	26	1204	32	1060	33	1367	35	658	48	635	59	1317	37	944	45	1840	34	1234	45	88	.	3140	23	240	.	689	45	2863	20	1630	33	1942	27	1187	39	790	58	919	47	883	55	427	70	0	.	17	80	3001	23	1499	35	1719	37	417	56	3652	22	2315	29	0	.	234	.	168	.	0	.	195103	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	213	37	168	43	287	45	132	28	0	.	0	.	61	46	138	30	765	18	0	.	87	44	68	63	88	38	0	.	83	70	102	46	0	.	199	55	0	.	0	.	26	75	54	59	0	.	0	.	0	.	201	27	115	54	294	36	15	79	68	45	0	.	35	48	-2	.	0	.	0	.	0	.	70	83	19	76	144	60	35	95	81	55	0	.	246	32	76	46	20	63	72	67	56	46	46	97	0	.	0	.	161	36	301	35	221	40	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	29	73	0	.	47	72	55	56	80	57	0	.	53	64	57	69	-1	498	43	56	50	69	0	.	59	65	44	59	54	47	54	73	4	72	0	.	35	86	0	.	0	.	149	48	18	77	56	58	109	45	39	72	55	37	102	40	75	57	154	45	0	.	6164	6
	21-30 cm	301	29	430	41	269	32	416	48	0	.	0	.	131	56	356	36	1547	16	25	.	92	50	226	42	209	42	2	.	75	52	318	43	0	.	357	45	0	.	0	.	48	75	39	53	0	.	0	.	0	.	384	26	245	35	334	32	54	88	40	59	0	.	83	55	23	.	0	.	0	.	0	.	43	87	115	61	100	74	37	74	172	70	0	.	722	29	55	59	65	60	138	45	308	48	17	100	0	.	8	100	290	37	338	44	458	35	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	179	84	47	.	71	72	151	66	101	58	0	.	99	67	143	57	53	71	58	51	33	52	0	.	169	65	112	50	138	59	155	50	97	51	0	.	52	77	0	.	0	.	127	61	35	71	94	64	154	41	121	75	114	41	349	41	173	43	322	36	0	.	12018	6
	31-40 cm	480	27	383	32	489	32	568	31	0	.	0	.	265	50	454	33	1632	15	0	.	88	66	282	39	439	38	23	.	204	57	351	47	0	.	496	36	0	.	0	.	36	60	58	77	0	.	0	.	0	.	793	30	393	38	710	39	68	71	59	57	0	.	110	66	11	.	0	.	0	.	0	.	58	100	60	82	168	59	13	216	132	55	0	.	676	28	180	39	129	48	364	39	372	39	37	74	0	.	176	75	375	53	489	30	449	36	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	133	75	20	.	79	80	90	52	52	103	0	.	93	71	152	60	53	71	45	52	101	66	0	.	61	53	175	47	254	49	127	42	80	72	0	.	80	65	0	.	0	.	47	63	44	100	74	72	365	41	47	71	465	38	340	34	460	42	238	37	0	.	15745	5
	41-50 cm	768	26	295	32	386	39	1042	26	0	.	0	.	617	49	371	37	2668	14	0	.	80	53	345	48	246	37	38	.	255	63	340	51	0	.	349	35	0	.	0	.	111	73	50	67	0	.	0	.	0	.	1147	24	675	39	636	31	52	74	142	57	0	.	195	52	28	.	0	.	0	.	0	.	0	.	3	862	108	78	39	74	80	61	0	.	1005	28	148	54	268	65	349	38	214	51	34	100	0	.	100	74	222	61	519	35	533	31	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	71	79	124	.	51	84	124	80	56	62	0	.	117	56	218	53	47	100	194	67	51	72	0	.	38	58	213	64	294	47	245	48	113	69	0	.	125	67	0	.	0	.	70	62	121	71	121	75	416	34	25	100	373	38	316	37	402	39	360	34	0	.	18746	5
	51-60 cm	446	36	446	31	283	42	1130	29	0	.	0	.	336	54	538	33	2831	16	0	.	249	49	111	69	284	42	70	.	130	71	306	44	0	.	493	33	0	.	0	.	39	72	81	61	0	.	0	.	0	.	907	27	623	52	542	35	44	100	98	58	0	.	188	85	0	.	0	.	0	.	0	.	0	.	130	100	71	66	67	100	174	53	0	.	455	33	490	49	91	71	247	77	121	55	58	100	0	.	71	71	112	45	650	37	517	30	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	48	100	22	.	0	.	16	100	227	80	0	.	89	80	20	100	93	89	72	72	20	100	0	.	38	71	284	57	310	56	127	59	50	71	0	.	159	60	0	.	0	.	21	100	18	100	270	55	302	36	0	.	418	37	658	41	336	41	433	38	0	.	17465	6
	61-70 cm	360	37	232	44	124	51	910	29	0	.	0	.	180	73	382	41	1699	21	0	.	242	53	142	82	148	59	0	.	68	100	62	75	0	.	119	50	0	.	0	.	0	.	0	.	0	.	0	.	0	.	331	36	336	45	387	39	93	100	101	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	121	72	0	.	538	39	287	47	0	.	167	57	29	100	39	100	0	.	42	100	64	71	219	47	237	63	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	19	100	0	.	0	.	27	100	27	100	0	.	42	100	0	.	33	100	30	100	0	.	0	.	0	.	0	.	52	100	61	71	58	100	0	.	178	82	0	.	0	.	50	76	91	100	210	52	102	100	0	.	82	72	186	53	104	75	241	57	0	.	9254	8
	71-80 cm	202	51	138	58	209	60	453	39	0	.	0	.	0	.	191	60	661	34	0	.	60	100	45	100	168	62	44	.	0	.	57	100	0	.	53	100	0	.	0	.	30	100	0	.	0	.	0	.	0	.	66	71	0	.	47	100	0	.	0	.	0	.	90	71	0	.	0	.	0	.	0	.	0	.	42	100	85	75	0	.	162	74	0	.	132	58	196	50	0	.	0	.	0	.	0	.	0	.	0	.	28	100	218	60	133	73	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	26	100	0	.	37	100	45	100	34	100	0	.	49	100	0	.	0	.	45	100	0	.	0	.	0	.	54	100	0	.	0	.	20	100	0	.	0	.	0	.	0	.	19	100	0	.	0	.	0	.	0	.	0	.	95	71	90	71	43	100	0	.	4068	12
	81-90 cm	41	100	53	100	87	71	161	73	0	.	0	.	0	.	0	.	213	50	0	.	0	0	58	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	63	100	0	.	0	.	0	.	46	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	67	100	0	.	0	.	66	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	116	100	259	59	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	101	71	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	42	100	0	.	0	.	0	.	0	.	0	.	50	100	0	.	80	100	100	71	85	71	0	.	0	.	1687	20
	91-100 cm	0	.	0	.	0	.	0	.	0	.	0	.	0	.	79	100	204	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	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	168	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	68	100	0	.	0	.	0	.	0	.	0	.	0	.	56	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	575	45
	>100 cm	0	.	0	.	0	.	86	100	0	.	0	.	0	.	74	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	67	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	.	400	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	.	627	67
	total	2811	21	2146	23	2133	26	4897	21	0	.	0	.	1591	47	2583	28	12221	12	25	.	898	38	1278	37	1582	31	177	.	815	50	1536	37	0	.	2134	29	0	.	0	.	289	53	346	59	0	.	0	.	0	.	3875	21	2387	33	2951	25	326	71	507	49	0	.	701	51	60	.	0	.	0	.	0	.	172	73	371	67	678	45	192	75	990	50	0	.	3775	21	1497	38	572	53	1337	36	1099	38	231	79	0	.	398	76	1252	36	3018	28	3207	25	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	505	71	214	.	286	71	508	54	578	57	0	.	541	56	590	47	278	66	656	51	255	56	0	.	364	54	882	45	1102	42	770	42	478	61	0	.	672	58	0	.	0	.	482	45	326	72	826	44	1498	29	231	70	1586	31	2147	31	1724	32	1792	28	0	.	86349	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	54	0	.	0	.	0	.	0	.	165	69	15	86	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	14	.	16	81	161	49	52	53	259	37	161	36	607	26	176	39	150	51	336	31	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	7	74	0	.	0	.	33	.	0	.	0	.	0	.	138	49	61	48	29	47	0	.	0	.	0	.	0	.	0	.	1	100	0	.	0	.	0	.	2410	11
	21-30 cm	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	132	49	0	.	0	.	0	.	0	.	277	48	20	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	.	30	.	19	100	70	95	82	65	211	46	350	38	810	23	177	38	362	51	431	28	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	98	74	0	.	0	.	26	.	0	.	0	.	0	.	137	52	86	49	43	55	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	3361	10
	31-40 cm	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	206	53	0	.	0	.	0	.	0	.	193	47	23	75	0	.	0	.	0	.	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	.	11	100	61	51	130	65	148	38	318	42	629	23	146	53	183	44	394	46	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	37	81	0	.	0	.	13	.	0	.	0	.	0	.	148	48	88	55	24	74	0	.	0	.	0	.	0	.	0	.	74	100	0	.	0	.	0	.	2841	11
	41-50 cm	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	178	65	0	.	0	.	0	.	0	.	103	49	55	85	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	18	100	76	54	59	73	31	72	185	31	429	37	52	64	114	43	253	38	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	44	71	0	.	0	.	0	.	0	.	0	.	0	.	64	54	49	65	-9	515	0	.	0	.	0	.	0	.	0	.	62	75	0	.	0	.	0	.	1762	14
	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	.	104	66	31	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	.	23	.	0	.	0	0	0	.	89	58	127	50	196	55	95	54	43	100	172	49	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	134	77	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	1065	20
	61-70 cm	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	35	100	0	.	0	.	0	.	0	.	30	71	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	.	0	.	0	.	0	.	30	100	0	0	0	.	19	100	65	65	133	48	15	100	21	100	37	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	.	0	.	0	.	0	.	0	.	401	25
	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	.	20	100	9	100	0	.	47	71	15	100	31	100	24	100	62	57	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	209	32
	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	.	39	100	16	100	0	.	0	.	27	100	26	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	.	30	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	164	42
	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	.	53	100	0	.	0	.	0	.	29	100	0	.	0	.	20	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	102	62
	>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	.	31	100	0	.	0	.	0	.	36	100	166	100	0	.	183	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	.	417	49
	total	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	632	51	0	.	0	.	0	.	0	.	873	39	160	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	.	83	.	93	96	511	42	349	56	756	34	1253	31	2910	19	884	33	897	36	1915	28	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	186	71	0	.	0	.	72	.	0	.	0	.	0	.	620	40	284	50	117	54	0	.	0	.	0	.	0	.	0	.	137	87	0	.	0	.	0	.	12732	8
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	230	35	168	43	287	45	167	26	48	62	207	36	1352	13	708	15	1127	16	727	18	87	44	91	49	229	26	0	.	120	52	295	24	439	23	296	40	30	54	248	29	437	22	382	20	686	20	1203	16	1136	14	752	15	360	28	448	25	525	18	143	37	238	31	75	33	101	36	174	35	219	37	210	32	293	31	173	36	233	40	392	24	259	32	176	27	326	26	209	30	162	41	134	44	127	31	333	28	243	38	141	45	301	27	301	35	262	34	207	38	367	27	153	26	476	25	336	26	703	23	643	19	439	28	516	24	217	33	188	45	248	30	226	30	195	30	278	33	153	47	65	61	260	28	50	50	86	48	241	26	155	43	207	35	113	31	166	45	89	54	8	100	45	68	985	15	964	18	994	17	91	35	148	43	83	76	195	27	162	48	103	40	80	54	164	43	0	.	28812	2
	21-30 cm	392	26	444	40	269	32	511	40	340	38	604	27	2691	12	1826	15	2141	14	2037	16	105	45	306	34	471	27	2	.	251	46	909	27	959	27	659	33	132	49	885	27	904	22	752	23	916	19	2203	14	2028	12	1210	15	563	23	675	23	1041	20	227	55	346	27	159	42	164	37	387	34	608	30	454	35	787	25	390	33	468	33	674	26	536	36	640	23	1022	25	240	34	318	34	212	37	539	33	418	33	476	31	376	37	572	28	338	44	623	31	145	48	544	27	361	26	551	28	816	28	958	21	1066	21	885	27	753	22	610	36	264	40	413	30	387	32	221	35	489	50	293	49	143	57	580	27	87	48	85	48	508	28	468	34	479	33	241	39	400	37	215	45	37	98	101	63	1672	15	1632	18	1774	16	316	33	257	39	174	37	664	30	447	30	349	41	203	40	330	36	0	.	57120	2
	31-40 cm	577	24	383	32	489	32	640	29	764	30	1199	25	4445	11	2756	13	2437	14	2641	15	111	56	381	34	691	31	23	.	461	39	1116	24	971	24	993	24	206	53	881	30	1625	17	1098	19	1206	21	3123	13	3157	14	2721	15	974	25	1361	26	1474	21	255	42	641	34	240	44	325	38	552	24	858	29	417	32	950	24	548	31	835	29	1113	23	698	28	1226	22	1124	22	563	35	693	29	442	34	625	29	558	25	714	27	712	32	841	31	489	30	589	30	236	41	533	27	597	33	322	27	582	27	789	21	670	23	440	27	779	29	504	33	360	44	546	36	514	28	463	38	467	35	361	42	152	60	797	25	145	71	194	44	650	24	347	27	609	28	504	33	316	41	171	50	234	55	108	55	2114	15	1686	16	2051	15	300	43	429	37	420	36	707	27	1024	25	414	33	550	39	250	35	0	.	77247	2
	41-50 cm	930	24	310	31	386	39	1315	22	899	28	1464	26	5786	12	3084	13	3828	12	2865	15	172	59	383	44	629	31	38	.	472	43	1115	26	1089	28	1040	25	178	65	1656	20	2377	17	1173	19	1714	21	3111	13	3378	13	3407	14	1227	25	1457	21	2094	20	347	37	680	31	397	36	348	39	970	25	493	32	300	35	1037	25	758	31	838	31	827	25	569	37	1719	21	1339	24	440	30	791	32	482	32	760	26	904	26	713	27	745	29	586	33	519	35	641	27	145	41	548	23	891	31	163	39	352	26	491	32	508	25	404	26	502	27	373	37	496	45	661	35	676	39	537	31	514	34	311	42	276	46	709	25	201	65	181	43	721	24	292	36	795	29	674	28	418	42	375	43	153	69	147	60	2025	17	1722	17	2069	16	486	38	371	40	582	30	832	25	1093	24	378	33	510	37	378	32	0	.	87743	2
	51-60 cm	664	31	446	31	283	42	1394	26	767	32	1309	29	5242	13	3845	13	4013	14	1891	19	269	46	131	61	778	30	70	.	228	49	864	26	1011	26	1032	24	52	100	1250	23	1712	19	1155	21	1831	21	3007	15	2576	15	2363	15	1110	33	1392	23	1752	23	220	42	580	41	339	56	263	41	789	27	477	39	236	52	905	29	809	35	291	34	840	29	1102	30	1695	21	656	29	893	33	244	45	582	47	419	32	646	27	840	30	697	30	516	38	650	37	608	27	313	37	763	28	487	38	228	34	192	43	226	49	447	29	286	37	399	31	361	38	221	42	342	39	480	38	697	37	652	43	299	44	42	71	560	28	149	62	199	50	365	28	576	34	667	35	782	37	271	47	159	46	260	52	290	46	1793	17	1396	20	2188	17	309	40	516	39	375	32	836	32	823	28	658	41	336	41	523	36	0	.	78198	2
	61-70 cm	425	35	232	44	124	51	1005	26	395	40	728	37	2605	17	2295	18	2284	17	585	30	242	53	176	68	403	41	0	.	130	62	435	38	751	39	394	34	35	100	565	32	856	25	764	25	1022	23	1429	17	1024	22	1030	23	920	33	1069	27	882	28	280	49	199	46	134	71	113	74	684	29	209	42	128	55	523	37	296	38	200	54	575	37	389	41	1274	30	568	37	437	38	108	58	250	45	137	51	716	32	229	48	344	40	118	50	219	47	329	50	225	61	284	40	375	37	124	56	156	43	215	48	278	38	74	58	330	54	210	43	180	48	164	52	309	38	377	39	504	48	171	45	0	.	547	46	50	72	146	78	220	36	260	54	53	71	209	44	61	71	251	47	0	.	203	73	986	31	639	25	946	24	223	60	617	42	136	79	521	34	232	47	186	53	104	75	272	52	0	.	42102	3
	71-80 cm	202	51	138	58	209	60	453	39	149	75	130	74	1055	22	1540	20	1272	25	237	41	60	100	90	70	281	55	44	.	0	.	199	55	269	53	190	56	0	.	545	39	881	29	350	35	475	32	790	28	466	30	520	32	234	67	358	45	405	48	129	74	84	71	90	71	197	59	97	71	25	100	147	66	333	42	331	51	193	47	391	46	703	38	781	33	132	58	265	45	0	.	63	100	0	.	465	43	51	100	211	84	67	71	218	60	175	61	303	40	235	51	195	48	29	100	83	59	15	100	204	42	101	50	165	45	195	42	92	100	171	64	151	52	186	41	63	71	85	71	0	.	88	71	45	100	53	100	90	72	83	100	98	71	137	61	0	.	20	100	111	100	163	79	1036	25	154	45	617	30	100	77	93	71	51	100	82	71	40	100	95	71	90	71	43	100	0	.	22251	5
	81-90 cm	41	100	53	100	87	71	224	60	0	.	0	.	575	38	619	34	495	36	175	72	0	0	58	100	0	.	0	.	0	.	71	100	91	72	0	.	0	.	227	44	154	59	308	43	370	37	690	28	304	42	145	58	0	.	0	.	42	100	56	100	62	100	0	.	0	.	0	.	0	.	0	.	0	.	79	100	0	.	44	100	185	58	371	80	0	.	66	100	52	100	0	.	0	.	66	100	53	100	92	74	56	100	116	100	259	59	0	.	165	60	135	64	87	76	29	100	27	100	56	71	0	.	68	72	0	.	0	.	46	100	170	60	156	74	49	100	102	73	0	.	0	.	101	71	0	.	67	100	0	.	0	.	72	100	0	.	0	.	81	100	42	100	458	39	190	49	155	45	0	.	113	72	50	100	47	100	80	100	100	71	85	71	0	.	0	.	9013	9
	91-100 cm	0	.	0	.	0	.	54	100	0	.	0	.	77	71	79	100	292	61	65	100	0	.	0	.	0	.	0	.	0	.	0	.	48	100	0	.	0	.	144	59	92	100	0	.	61	100	117	72	61	100	69	100	53	100	0	.	0	.	0	.	84	100	72	100	0	.	0	.	0	.	0	.	0	.	0	.	55	100	0	.	0	0	81	100	0	.	0	.	0	.	0	.	0	.	65	100	0	.	41	100	0	.	168	100	0	.	37	100	53	100	0	.	0	.	0	0	29	100	75	100	0	.	20	100	0	.	47	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	68	100	0	.	0	.	0	.	0	.	0	.	0	.	116	71	0	.	0	.	142	60	94	71	0	.	0	.	0	.	46	100	0	.	0	.	0	.	0	.	0	.	0	.	2506	17
	>100 cm	0	.	67	100	0	.	86	100	0	.	0	.	0	.	200	73	68	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	67	100	0	.	51	100	0	.	0	.	127	71	318	46	52	100	67	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	36	100	0	.	62	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	43	100	0	.	0	.	400	100	163	100	148	82	0	.	0	.	0	.	36	100	166	100	0	.	183	59	0	.	0	.	0	.	0	.	38	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	38	100	0	.	53	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	2470	23
	total	3462	19	2241	23	2133	26	5849	19	3362	28	5641	22	23829	9	16952	10	17958	10	11223	12	1046	35	1615	31	3482	24	177	.	1662	34	5005	21	5629	18	4671	20	632	51	6452	18	9039	14	5981	16	8408	15	15991	10	14180	10	12284	12	5441	20	6759	18	8215	17	1656	32	2915	24	1505	33	1512	32	3653	22	2890	26	1892	30	4828	21	3385	25	3112	25	4893	20	4442	23	8026	18	5169	18	3113	24	2368	25	2166	28	2607	24	4170	21	3319	23	3403	24	3056	25	3018	28	3885	22	1773	27	3642	20	3195	23	1980	21	2546	22	3490	17	4113	16	2628	21	3715	20	2469	28	1847	33	2591	28	2913	25	2870	25	3015	28	1776	36	679	42	3540	21	896	46	944	36	2863	20	2181	27	2908	23	2732	25	1633	35	1397	37	883	55	1099	45	11249	12	8475	13	10848	12	1826	31	2545	29	1915	26	3884	21	3900	21	2284	29	1958	30	1960	27	0	.	407462	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. 2280622. Birmensdorf, Swiss Federal Research Institute WSL

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