Selection from the list of topics

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

1. What do the numbers stand for?

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

Example 1: Estimated value and standard error

NFI5

volume of deadwood (stemwood)
ownership (2 categories)

regional demarcation: production region

unit: m³/ha

evaluation area: accessible forest without shrub forest

grid: 1.4 km grid, subgrids 1-5

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

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

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2. What is the purpose of the standard error?

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

The statistical certainty is:

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

Example 2: Calculating confidence intervals

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

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

Procedure

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

Answer

			Step 1	Step 2

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

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

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

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

Data: see example 2

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

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

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3. When are two results statistically different?*

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

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

Example 4: Interpretation of two results from the same inventory

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

	case 2						case 1

case 1

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

Procedure

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

Answer

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

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

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

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

Case 2

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

Procedure

See case 1.

Answer

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

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

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

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

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

Example 5: Interpretation of two results from different inventories

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

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

Procedure

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

Answer

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

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

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

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

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

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

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

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

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

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

Procedure

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

Answer

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

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

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

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

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

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

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

Procedure

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

Answer

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

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

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

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

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

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

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

Example 8: Standard error and combination of variable expressions

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

The standard error increases as the level of detail increases.

Large standard errors are to be expected if:

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

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

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

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5. Two types of changes?

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

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

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

The results are:

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

Example 9: : Additivity/non-additivity of changes

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

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

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

Example 10: Average number of years per domain

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

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

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

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

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

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

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

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

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

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

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NFI2
growing stock (stemwood)
altitudinal vegetation belts (NaiS; 6 classes) · diameter at breast height (10 classes)
regional demarcation: forest district (2024)
unit: 1000 m³
evaluation area: accessible forest without shrub forest NFI1-NFI5
grid: 1.4 km grid, subgrids 1-5
state 1993/95
		forest district (2024)
		AG01		AG02		AG03		AG04		AI01		AR01		BE01		BE02		BE03		BE04		BSBL01		BSBL02		BSBL03		BSBL04		FR01		FR02		FR03		FR04		GE01		GL01		GR01		GR02		GR03		GR04		GR05		JU01		LU01		LU02		LU03		NE01		NE02		NE03		NE04		NE06		NW01		OW01		OW02		SG01		SG02		SG03		SG04		SG05		SH01		SO01		SO02		SO03		SO04		SZ01		SZ02		SZ03		TG01		TG02		TG03		TI01		TI02		TI03		TI04		TI05		TI06		TI07		TI08		TI09		UR01		UR02		UR03		VD02		VD03		VD04		VD05		VD06		VD07		VD08		VD09		VD11		VD12		VD14		VD15		VD16		VD18		VD20		VD22		VS01		VS02		VS03		ZG01		ZH01		ZH02		ZH03		ZH04		ZH05		ZH06		ZH07		lakes		Switzerland
altitudinal vegetation belts (NaiS; 6 classes)	diameter at breast height (10 classes)	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%
n/a	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	12-20 cm	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	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	.	0	.	0	.	6	.	8	63	251	27	0	.	0	.	0	.	0	.	0	.	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	76	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	.	85	59	26	49	3	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	404	21
	21-30 cm	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	18	.	0	.	5	.	33	61	415	24	0	.	0	.	0	.	0	.	0	.	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	25	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	.	168	34	121	66	27	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	826	18
	31-40 cm	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	16	.	0	.	0	.	56	63	632	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	.	0	.	20	100	28	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	.	234	36	68	77	8	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	1063	19
	41-50 cm	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	9	.	0	.	0	.	108	43	487	27	0	.	0	.	0	.	0	.	0	.	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	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	.	279	32	59	51	7	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	973	17
	51-60 cm	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	37	.	0	.	0	.	68	79	396	33	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	13	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	104	44	52	61	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	670	23
	61-70 cm	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	22	.	0	.	0	.	71	74	141	51	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	104	53	23	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	360	30
	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	.	60	72	143	56	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	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	58	16	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	272	36
	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	.	73	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	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	24	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	97	59
	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	.	35	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	35	100
	>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	.	33	100	51	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	.	37	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	121	59
	total	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	103	.	0	.	11	.	437	47	2590	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	.	0	.	64	82	83	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	.	1124	26	366	46	46	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	4822	13
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	.	199	24	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	7	100	85	47	27	56	52	36	139	32	268	37	0	.	0	.	0	.	5	.	0	.	0	.	0	.	0	.	0	.	48	95	35	84	51	73	0	.	0	.	-4	264	0	.	19	.	0	.	0	.	0	.	0	.	0	.	3	100	0	.	0	.	0	.	0	.	0	.	0	0	49	42	42	66	3	.	0	.	0	.	52	66	1	100	0	.	0	.	13	71	18	100	13	.	0	.	1	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	10	.	0	.	0	.	0	.	0	.	165	28	172	32	135	48	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	1609	11
	21-30 cm	0	.	0	.	0	.	0	.	0	.	0	.	740	22	7	76	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	251	31	82	51	229	38	476	31	721	27	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	49	84	55	100	126	71	0	.	0	.	92	63	0	.	-5	.	0	.	0	.	0	.	0	.	0	.	7	100	0	.	0	.	0	.	0	.	0	.	8	100	131	48	45	60	9	.	0	.	0	.	48	54	6	100	0	.	6	.	41	100	5	100	9	.	12	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	10	.	0	.	0	.	0	.	0	.	368	30	434	30	250	38	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	4212	9
	31-40 cm	0	.	0	.	0	.	0	.	0	.	0	.	989	26	75	71	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	32	77	332	30	150	55	546	34	425	32	998	25	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	49	71	64	69	93	61	0	.	8	.	60	76	0	.	2	.	0	.	0	.	0	.	0	.	0	.	97	86	0	.	0	.	0	.	0	.	0	.	65	71	242	37	100	65	0	.	0	.	0	.	72	53	17	73	0	.	0	.	56	87	17	100	0	.	49	75	1	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	30	.	0	.	0	.	0	.	0	.	555	30	478	30	455	45	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	6056	9
	41-50 cm	0	.	0	.	0	.	0	.	0	.	0	.	948	32	27	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	52	71	610	29	110	61	698	29	634	33	1166	20	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	9	100	78	80	25	72	0	.	15	.	146	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	22	100	0	.	0	.	0	.	0	.	0	.	48	64	247	43	102	61	0	.	0	.	0	.	77	78	21	71	0	.	15	.	83	100	22	100	26	.	11	100	49	75	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	44	.	0	.	0	.	0	.	0	.	756	29	656	34	403	31	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	7102	9
	51-60 cm	0	.	0	.	0	.	0	.	0	.	0	.	496	27	34	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	115	76	369	41	52	82	435	30	384	31	1127	26	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	67	100	16	100	51	100	0	.	21	.	16	100	0	.	-14	.	0	.	0	.	0	.	0	.	0	.	65	78	0	.	0	.	0	.	0	.	0	.	143	66	181	46	40	71	0	.	0	.	0	.	115	57	18	100	0	.	3	.	76	78	18	100	66	.	-11	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	29	.	0	.	0	.	0	.	0	.	633	31	379	40	455	37	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	5378	10
	61-70 cm	0	.	0	.	0	.	0	.	0	.	0	.	249	41	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	315	40	43	71	207	45	218	52	157	46	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	15	100	0	.	28	100	0	.	29	.	55	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	54	100	0	.	0	.	0	.	0	.	0	.	19	100	51	71	0	.	0	.	0	.	0	.	45	72	31	100	0	.	27	.	22	100	0	.	0	.	21	100	27	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	466	42	55	71	225	45	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	2360	14
	71-80 cm	0	.	0	.	0	.	0	.	0	.	0	.	53	71	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	68	71	193	52	0	.	74	65	53	71	112	52	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	0	0	.	0	.	0	.	0	.	0	.	0	.	0	.	34	100	0	.	0	.	0	.	0	.	0	.	37	100	30	100	0	.	0	.	0	.	0	.	41	100	0	.	0	.	31	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	379	39	33	100	0	0	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	1138	20
	81-90 cm	0	.	0	.	0	.	0	.	0	.	0	.	30	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	29	100	50	100	26	100	59	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	.	0	.	37	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	112	58	65	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	409	31
	91-100 cm	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	61	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	46	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	47	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	155	58
	>100 cm	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	56	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	56	100
	total	0	.	0	.	0	.	0	.	0	.	0	.	3704	21	143	76	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	304	60	2205	25	491	45	2416	25	2329	25	4550	19	0	.	0	.	0	.	5	.	0	.	0	.	0	.	0	.	0	.	237	71	248	67	374	59	0	.	74	.	410	64	0	.	2	.	0	.	0	.	0	.	0	.	0	.	282	71	0	.	0	.	0	.	0	.	0	.	320	60	931	33	329	53	12	.	0	.	0	.	449	47	94	71	0	.	81	.	292	75	80	80	115	.	83	81	116	86	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	123	.	0	.	0	.	0	.	0	.	3481	22	2271	27	1923	29	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	28474	7
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	.	301	29	14	60	0	.	2	100	0	.	0	.	0	.	0	.	10	.	64	60	122	73	12	79	0	.	14	76	50	41	216	46	217	31	416	20	333	28	0	.	17	.	0	.	71	52	0	.	0	.	0	.	0	.	0	.	-11	.	112	47	10	71	0	.	18	100	9	58	3	.	5	100	0	.	0	.	0	.	0	.	0	.	21	60	81	76	6	70	0	.	0	.	0	.	69	44	61	50	55	47	7	63	0	.	0	.	32	65	21	73	24	81	25	70	21	84	218	49	20	76	13	54	61	88	0	.	0	.	0	0	0	.	0	.	0	.	0	.	0	.	20	93	0	.	0	.	0	.	0	.	495	27	414	24	276	34	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	3948	8
	21-30 cm	0	.	0	.	0	.	0	.	0	.	0	.	752	22	129	63	0	.	9	100	0	.	0	.	0	.	0	.	43	.	219	65	103	70	15	100	0	.	75	78	286	28	338	39	504	26	1239	21	828	27	0	.	22	.	0	.	231	70	0	.	0	.	0	.	0	.	0	.	20	.	229	52	47	49	0	.	25	100	32	78	20	.	-16	100	0	.	0	.	0	.	0	.	0	.	40	56	147	83	27	100	0	.	0	.	0	.	37	54	33	137	212	40	37	72	0	.	0	.	107	49	84	54	42	114	49	66	131	84	367	45	22	60	71	54	143	91	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	48	100	0	.	0	.	0	.	0	.	625	22	598	25	621	26	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	8591	7
	31-40 cm	0	.	0	.	0	.	0	.	0	.	0	.	1314	20	154	69	0	.	0	.	0	.	0	.	0	.	0	.	58	.	171	65	156	67	49	71	0	.	106	74	763	37	224	39	618	29	1969	19	1279	22	0	.	35	.	0	.	106	51	0	.	0	.	0	.	0	.	0	.	35	.	188	50	153	58	0	.	67	100	14	102	62	.	11	100	0	.	0	.	0	.	0	.	0	.	115	54	127	72	66	86	0	.	0	.	0	.	94	55	88	75	411	44	15	71	0	.	0	.	78	67	51	76	127	72	111	60	151	94	438	43	127	78	317	71	49	132	0	.	0	.	66	100	0	.	0	.	0	.	0	.	0	.	93	66	0	.	0	.	0	.	0	.	935	26	760	26	661	25	44	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	12456	7
	41-50 cm	0	.	0	.	0	.	0	.	0	.	0	.	1697	21	155	64	0	.	0	.	0	.	0	.	0	.	0	.	27	.	175	62	171	57	33	76	0	.	56	63	762	33	352	33	1149	27	2291	18	1060	22	0	.	12	.	0	.	188	52	0	.	0	.	0	.	0	.	0	.	21	.	182	46	181	69	0	.	56	100	0	0	44	.	101	100	0	.	0	.	0	.	0	.	0	.	108	56	125	57	89	83	0	.	0	.	0	.	177	49	48	63	465	33	39	78	0	.	0	.	21	100	81	88	82	71	103	76	128	80	292	44	306	65	139	59	80	71	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	53	60	0	.	0	.	0	.	0	.	580	29	876	23	836	24	98	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	13438	6
	51-60 cm	0	.	0	.	0	.	0	.	0	.	0	.	1740	21	118	74	0	.	11	100	0	.	0	.	0	.	0	.	55	.	-6	100	46	72	34	71	0	.	63	74	641	40	271	37	836	26	1705	18	570	31	0	.	0	.	0	.	56	71	0	.	0	.	0	.	0	.	0	.	0	.	119	50	144	48	0	.	0	.	30	73	0	.	48	100	0	.	0	.	0	.	0	.	0	.	103	86	33	100	24	100	0	.	0	.	0	.	156	59	129	52	266	40	15	100	0	.	0	.	18	100	57	71	112	81	79	71	42	100	149	61	101	60	69	73	202	74	0	.	0	.	13	100	0	.	0	.	0	.	0	.	0	.	44	100	0	.	0	.	0	.	0	.	386	34	471	28	724	30	11	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	9685	8
	61-70 cm	0	.	0	.	0	.	0	.	0	.	0	.	481	27	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	48	100	14	100	0	.	198	84	333	37	166	63	455	35	838	25	139	45	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	150	53	71	75	0	.	0	.	29	100	12	.	54	100	0	.	0	.	0	.	0	.	0	.	27	100	0	.	0	.	0	.	0	.	0	.	251	56	175	77	156	61	39	70	0	.	0	.	20	100	50	72	48	100	25	100	0	.	0	.	19	100	30	100	0	.	0	.	0	.	43	100	0	.	0	.	0	.	0	.	0	.	27	100	0	.	0	.	0	.	0	.	228	56	184	42	306	34	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	4619	11
	71-80 cm	0	.	0	.	0	.	0	.	0	.	0	.	191	46	0	.	0	.	77	100	0	.	0	.	0	.	0	.	0	.	0	.	26	100	0	.	0	.	120	63	107	58	148	78	187	46	759	32	66	72	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	0	23	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	36	100	0	.	0	.	0	.	0	.	39	100	145	64	0	.	0	.	0	.	25	100	0	.	42	100	33	100	0	.	32	100	28	100	39	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	263	45	115	62	118	66	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	2619	15
	81-90 cm	0	.	0	.	0	.	0	.	0	.	0	.	52	100	0	.	0	.	49	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	77	71	0	.	0	.	48	100	37	100	37	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	42	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	27	100	0	.	0	.	0	.	0	.	0	.	73	100	0	.	0	.	0	.	0	.	0	.	26	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	40	100	44	100	27	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	578	28
	91-100 cm	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	86	71	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	69	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	60	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	37	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	0	39	100	48	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	340	39
	>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	.	149	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	.	69	100	0	.	0	.	0	.	0	.	0	.	96	100	0	.	0	.	0	.	0	.	0	.	0	.	44	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	.	358	46
	total	0	.	0	.	0	.	0	.	0	.	0	.	6528	18	570	51	0	.	148	92	0	.	0	.	0	.	0	.	194	.	622	58	672	54	158	72	0	.	795	54	2942	26	1715	30	4013	21	9403	14	4313	18	0	.	87	.	0	.	652	46	0	.	0	.	0	.	0	.	0	.	65	.	981	42	606	49	0	.	167	100	248	53	142	.	202	100	0	.	0	.	0	.	0	.	0	.	414	48	514	58	248	73	0	.	0	.	0	.	941	37	573	53	1709	32	152	69	0	.	0	.	470	56	343	57	476	65	425	64	510	77	1496	38	649	57	723	53	533	68	0	.	0	.	122	100	0	.	0	.	0	.	0	.	0	.	285	60	0	.	0	.	0	.	0	.	3553	19	3502	19	3618	20	153	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	56633	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	81	56	4	.	0	.	52	51	86	53	258	34	634	26	896	16	204	26	922	18	0	0	33	75	103	46	0	.	183	56	361	36	465	29	241	43	0	.	340	29	233	38	92	31	26	62	121	39	0	.	732	23	183	36	232	31	503	21	82	69	240	28	42	57	78	47	247	37	187	42	106	57	211	31	156	38	145	46	215	37	158	42	288	28	187	41	116	46	173	44	86	53	99	37	180	46	228	37	158	42	71	101	0	.	103	79	0	.	60	45	0	.	143	56	162	40	109	43	280	45	222	38	116	51	146	40	70	63	36	72	90	45	38	52	129	45	87	53	5	.	255	31	29	.	24	47	228	30	77	49	176	45	54	46	40	81	62	81	17	71	53	71	0	.	2	.	261	26	150	43	43	55	24	82	265	44	117	57	0	.	21	.	1	.	0	.	14138	4
	21-30 cm	88	56	4	.	0	.	143	52	430	33	933	28	1226	20	1823	17	626	30	2297	16	7	100	79	71	164	47	0	.	126	64	495	32	1056	27	503	35	0	.	857	37	232	38	232	33	17	74	191	38	0	.	1254	20	203	36	382	35	1131	23	134	53	492	30	146	49	228	43	415	31	486	34	37	93	474	33	517	31	309	41	641	26	304	48	1134	26	379	40	198	51	372	35	30	97	395	38	179	45	471	32	307	35	425	40	0	.	55	61	0	.	73	69	0	.	102	45	229	38	124	49	263	41	309	42	139	55	205	51	52	100	6	100	152	49	84	54	233	46	181	64	67	.	595	30	64	.	107	53	498	26	159	41	287	39	128	49	53	62	165	56	91	61	43	72	0	.	0	.	452	28	149	49	158	48	43	71	688	30	377	34	0	.	25	.	7	.	0	.	28929	4
	31-40 cm	248	53	0	.	0	.	314	43	720	30	1279	27	1747	21	3107	15	1258	25	2942	16	62	83	83	82	232	45	0	.	126	62	528	46	1444	25	773	42	0	.	1153	31	309	33	372	37	41	65	127	57	0	.	2473	19	697	32	805	27	1572	22	195	54	467	37	219	52	226	41	809	32	524	38	137	62	819	30	889	27	399	41	566	26	345	35	1303	26	486	39	185	56	633	36	205	58	601	35	326	42	732	27	477	34	249	39	0	.	132	66	0	.	76	63	0	.	81	52	130	45	74	58	181	41	146	53	206	69	217	41	64	52	159	63	144	68	69	58	307	41	280	49	208	.	659	27	48	.	192	46	437	27	323	41	534	34	199	48	208	74	188	60	131	54	278	85	0	.	0	.	637	28	207	46	227	44	155	58	995	25	611	29	0	.	164	.	51	.	0	.	41924	4
	41-50 cm	211	62	0	.	0	.	348	46	679	32	1583	25	2418	19	4027	13	1714	22	2317	16	42	71	43	103	336	40	0	.	40	74	680	31	1170	24	899	37	0	.	1083	24	225	54	480	33	108	71	59	80	0	.	1904	17	528	34	959	32	1947	22	246	43	555	30	250	46	252	40	882	25	328	42	271	62	1039	32	790	32	302	45	761	27	520	39	1678	26	189	47	477	35	512	40	480	47	541	36	406	34	1246	32	446	34	397	44	0	.	89	59	0	.	150	55	0	.	59	70	90	54	66	52	160	38	159	49	127	47	132	58	84	60	48	77	174	41	146	73	252	39	381	48	93	.	480	29	76	.	233	53	447	24	316	39	432	53	300	48	217	69	215	48	141	51	194	66	0	.	0	.	386	34	251	47	388	43	287	46	1153	28	668	34	0	.	29	.	98	.	0	.	44889	3
	51-60 cm	98	80	0	.	0	.	163	55	413	44	781	30	1848	20	3393	15	1351	24	1166	20	164	100	27	100	312	46	0	.	0	.	325	48	1037	29	273	50	0	.	585	31	218	45	614	32	19	100	109	74	0	.	1229	21	768	39	750	33	1596	25	165	56	308	41	178	67	233	59	775	30	287	45	161	56	757	40	576	36	284	53	772	37	466	39	1374	24	211	48	324	45	195	44	105	60	232	42	333	40	668	31	419	40	183	53	0	.	92	65	0	.	142	47	0	.	67	58	65	62	46	100	123	71	24	100	115	64	242	68	76	76	122	67	246	62	129	58	147	47	143	61	0	.	522	44	19	.	289	51	347	30	259	56	292	48	355	45	86	100	154	61	139	67	252	67	0	.	0	.	253	38	218	45	306	44	181	56	776	30	252	44	0	.	0	.	25	.	0	.	32748	4
	61-70 cm	0	.	0	.	0	.	0	.	181	60	96	59	705	30	1973	18	592	28	292	38	45	100	40	100	44	100	0	.	0	.	226	50	693	36	23	100	0	.	338	40	148	59	185	42	0	.	79	62	0	.	643	33	452	52	428	32	457	41	55	71	116	50	56	71	151	50	302	36	0	.	95	71	255	56	170	52	280	72	329	44	340	40	579	41	46	100	179	73	70	70	39	100	52	100	298	51	207	45	400	48	33	100	0	.	143	77	0	.	45	100	0	.	43	73	63	100	0	.	91	56	0	.	23	100	52	71	108	100	60	100	189	46	57	100	18	100	206	52	0	.	111	67	0	.	160	65	29	100	142	64	37	100	61	72	0	.	125	100	45	100	82	76	0	.	0	.	19	100	66	71	65	71	74	71	277	42	105	58	0	.	0	.	0	.	0	.	14190	6
	71-80 cm	0	.	84	.	0	.	55	100	127	76	0	.	187	51	759	26	400	43	135	58	46	100	0	.	50	100	0	.	0	.	0	.	96	58	28	100	0	.	156	53	0	.	103	79	83	72	32	100	0	.	144	51	0	.	0	.	124	71	77	71	109	72	0	.	121	75	52	100	0	.	0	.	29	100	88	71	38	100	71	71	224	48	334	54	0	.	37	100	81	71	0	.	0	.	88	71	56	100	74	74	33	100	0	.	0	.	0	.	67	100	0	.	26	100	20	100	0	.	20	100	0	.	20	100	0	.	42	100	27	100	0	.	37	100	0	.	102	71	0	.	33	100	0	.	0	.	95	71	0	.	0	.	0	.	0	.	90	72	115	100	0	.	0	.	0	.	71	71	42	100	130	72	28	100	102	61	50	100	0	.	0	.	0	.	0	.	5238	10
	81-90 cm	0	.	0	.	0	.	0	.	0	.	0	.	85	72	426	38	50	100	0	.	0	.	0	.	0	.	0	.	0	.	52	100	0	.	0	.	0	.	0	.	0	.	0	.	20	100	51	100	0	.	49	100	39	100	0	.	0	.	0	.	0	.	60	100	0	.	53	100	0	.	0	.	0	.	0	.	50	100	0	0	0	.	53	100	0	.	0	.	0	.	0	.	0	.	53	100	0	.	37	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	0	0	.	0	.	0	.	45	100	93	100	57	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	39	100	0	.	0	.	0	.	56	100	0	.	0	.	0	.	0	.	0	.	1366	20
	91-100 cm	0	.	0	.	0	.	67	100	0	.	0	.	0	.	75	100	0	.	57	100	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	.	80	100	0	.	0	.	0	0	63	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	124	71	0	.	0	.	0	.	0	.	85	100	0	.	0	.	41	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	60	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	709	31
	>100 cm	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	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	55	100
	total	726	48	93	.	0	.	1142	43	2635	28	4929	22	8906	16	16480	11	6197	19	10128	12	366	81	305	62	1241	38	0	.	476	52	2668	30	5962	21	2740	31	0	.	4511	23	1365	30	2077	26	314	58	769	38	0	.	8485	14	2870	29	3556	25	7330	18	955	45	2286	24	951	42	1290	36	3536	22	1813	31	807	49	3585	29	3266	25	1807	39	3354	23	2357	30	6807	20	1498	34	1517	32	2035	28	945	43	1919	30	1862	31	3610	26	2440	28	1392	33	0	.	614	55	0	.	698	48	0	.	522	38	800	36	418	39	1117	30	859	34	745	43	994	39	497	60	502	61	1089	36	617	53	1087	36	1380	44	373	.	2654	24	237	.	1006	42	2080	21	1276	38	1758	29	1098	37	604	59	999	51	678	55	902	63	0	.	2	.	2117	23	1082	37	1376	36	792	46	4311	22	2180	27	0	.	240	.	182	.	0	.	184187	3
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	221	26	412	39	239	54	192	34	0	.	0	.	79	56	189	34	1058	19	63	.	91	57	181	51	133	50	5	.	60	55	128	57	0	.	82	38	0	.	0	.	46	74	52	47	0	.	0	.	0	.	292	35	160	51	289	39	29	71	36	59	0	.	63	55	23	.	0	.	0	.	0	.	23	100	29	62	128	47	35	82	70	57	0	.	289	28	42	49	54	51	156	54	85	46	7	81	0	.	2	100	112	37	244	38	411	48	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	75	90	0	.	18	71	56	53	42	136	0	.	21	65	99	59	29	85	73	57	17	57	0	.	81	63	66	79	75	75	102	58	58	84	0	.	36	56	0	.	0	.	63	62	26	90	40	62	91	40	149	85	130	59	225	45	88	56	129	43	0	.	7594	7
	21-30 cm	451	32	424	32	229	41	516	28	0	.	0	.	227	52	483	29	2383	15	0	.	147	54	305	38	318	40	26	.	61	78	230	48	0	.	331	38	0	.	0	.	129	69	45	56	0	.	0	.	0	.	783	26	359	43	534	33	60	72	64	51	0	.	147	45	7	.	0	.	0	.	0	.	33	100	87	67	251	53	21	163	88	52	0	.	409	32	95	47	114	57	258	37	285	45	24	72	0	.	34	100	268	43	416	33	375	42	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	82	71	0	.	73	78	39	71	138	83	0	.	151	57	12	71	43	100	106	60	65	92	0	.	146	49	240	50	138	60	151	47	174	67	0	.	172	68	0	.	0	.	79	52	45	76	30	62	249	41	82	59	341	41	207	38	257	39	146	42	0	.	14182	5
	31-40 cm	935	25	577	30	551	36	1130	23	0	.	0	.	273	48	522	30	2794	14	0	.	190	50	401	45	462	36	46	.	331	51	362	42	0	.	713	32	0	.	0	.	107	78	125	63	0	.	0	.	0	.	1088	27	765	41	1109	26	55	100	120	50	0	.	149	54	76	.	0	.	0	.	0	.	77	100	79	85	294	54	91	71	120	66	0	.	887	27	134	58	237	65	403	39	347	39	10	100	0	.	196	71	291	44	371	33	555	31	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	25	100	0	.	48	72	88	85	109	69	0	.	97	66	43	123	12	100	390	56	117	73	0	.	175	54	131	48	351	44	146	56	57	64	0	.	257	65	0	.	0	.	15	100	59	71	78	62	641	38	58	100	354	39	421	32	467	40	384	42	0	.	21496	5
	41-50 cm	942	24	1035	30	253	40	1869	25	0	.	0	.	662	48	628	37	3655	14	0	.	301	56	174	50	269	56	16	.	334	52	394	58	0	.	684	36	0	.	0	.	134	54	138	68	0	.	0	.	0	.	1092	24	874	41	1096	29	61	73	134	52	0	.	178	56	0	.	0	.	0	.	0	.	55	100	83	100	264	54	83	79	121	62	0	.	782	29	540	44	151	62	579	43	212	54	52	100	0	.	34	71	520	50	829	34	474	29	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	-7	100	0	.	28	100	74	64	131	74	0	.	106	72	67	83	87	100	164	55	30	100	0	.	52	140	137	64	393	47	158	67	120	76	0	.	332	63	0	.	0	.	16	132	82	86	305	50	554	37	105	100	294	42	747	33	524	34	624	36	0	.	24819	5
	51-60 cm	963	30	899	30	275	40	1015	26	0	.	0	.	360	44	673	36	3047	17	0	.	321	40	57	59	152	46	0	.	219	52	142	48	0	.	448	37	0	.	0	.	77	80	159	55	0	.	0	.	0	.	759	25	427	40	654	30	82	100	61	55	0	.	85	82	0	.	0	.	0	.	0	.	0	.	54	100	84	71	19	100	112	63	0	.	559	26	421	63	1	100	319	53	55	72	27	100	0	.	20	100	279	51	447	39	512	35	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	51	100	0	.	0	.	38	72	68	76	0	.	171	75	0	.	72	100	40	78	0	.	0	.	171	63	0	.	49	100	50	71	90	72	0	.	115	53	0	.	0	.	38	77	22	100	145	58	410	43	25	100	545	43	433	37	514	54	358	44	0	.	17191	6
	61-70 cm	400	43	287	41	172	53	606	34	0	.	0	.	106	59	245	48	1310	24	0	.	194	58	112	100	92	74	0	.	75	73	61	75	0	.	78	71	0	.	0	.	43	100	0	.	0	.	0	.	0	.	193	41	31	100	212	46	73	100	0	.	0	.	39	100	0	.	0	.	0	.	0	.	0	.	38	100	48	100	0	.	146	78	0	.	209	52	204	54	0	.	135	60	0	.	0	.	0	.	0	.	147	59	225	53	307	45	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	28	100	69	70	22	100	0	.	143	76	0	.	0	.	69	70	0	.	0	.	0	.	35	100	0	.	0	.	71	72	0	.	0	.	0	.	0	.	58	100	0	.	0	.	175	57	0	.	77	100	175	45	82	59	202	56	0	.	6992	9
	71-80 cm	128	72	132	74	69	71	182	59	0	.	0	.	0	.	57	100	589	36	0	.	123	100	0	.	0	.	0	.	0	.	90	100	0	.	38	100	0	.	0	.	0	.	42	100	0	.	0	.	0	.	91	70	0	.	113	71	0	.	0	.	0	.	32	100	0	.	0	.	0	.	0	.	0	.	0	.	84	100	0	.	136	100	0	.	0	.	31	100	0	.	45	100	0	.	0	.	0	.	0	.	113	57	54	100	258	49	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	25	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	82	71	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	27	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	58	100	0	.	36	100	0	.	0	.	2636	16
	81-90 cm	0	.	33	100	0	.	53	100	0	.	0	.	0	.	156	58	332	45	0	.	0	.	62	100	0	.	0	.	0	.	55	100	0	.	123	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	98	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	58	100	99	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	.	48	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	91	71	43	100	0	.	0	.	1250	24
	91-100 cm	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	73	100	0	.	87	100	0	.	0	.	0	.	0	.	0	.	0	.	72	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	81	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	.	314	50
	>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	4040	21	3798	24	1787	30	5563	20	0	.	0	.	1707	43	2953	26	15241	11	63	.	1452	37	1291	37	1427	36	92	.	1080	46	1463	37	0	.	2570	29	0	.	0	.	536	56	561	53	0	.	0	.	0	.	4298	20	2712	31	4007	24	359	82	415	43	0	.	693	48	105	.	0	.	0	.	0	.	188	100	369	70	1154	47	249	76	793	60	0	.	3135	22	1468	42	557	52	1894	35	984	37	119	91	0	.	286	71	1787	36	2684	27	2972	24	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	251	72	0	.	195	76	365	58	511	62	0	.	689	55	222	57	244	72	924	45	228	76	0	.	624	51	609	49	1006	40	606	44	618	57	0	.	939	60	0	.	0	.	269	53	233	76	599	45	2120	33	419	65	1799	32	2299	28	2012	33	1843	31	0	.	96475	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	.	217	49	0	.	0	.	0	.	0	.	160	45	8	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	.	32	.	17	.	7	768	42	61	260	41	304	32	701	23	151	58	107	48	331	30	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	40	90	0	.	0	.	32	.	0	.	0	.	0	.	168	39	55	45	26	97	0	.	0	.	0	.	0	.	0	.	11	100	0	.	0	.	0	.	2668	10
	21-30 cm	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	255	49	0	.	0	.	0	.	0	.	244	52	7	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	6	.	16	.	72	43	71	61	147	45	415	29	618	25	118	45	95	45	446	34	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	61	73	0	.	0	.	31	.	0	.	0	.	0	.	137	47	114	57	51	58	0	.	0	.	0	.	0	.	0	.	27	100	0	.	0	.	0	.	2931	10
	31-40 cm	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	51	87	0	.	0	.	0	.	0	.	133	52	17	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	5	.	40	100	7	100	55	60	207	44	485	30	55	46	66	56	311	36	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	28	71	0	.	0	.	0	.	0	.	0	.	0	.	149	45	86	49	39	71	0	.	0	.	0	.	0	.	0	.	120	85	0	.	0	.	0	.	1854	13
	41-50 cm	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	70	85	0	.	0	.	0	.	0	.	101	65	53	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	.	44	.	0	.	25	73	48	100	56	88	49	56	199	39	47	54	27	162	163	49	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	4	100	0	.	0	.	0	.	0	.	0	.	0	.	92	55	0	.	22	100	0	.	0	.	0	.	0	.	0	.	76	71	0	.	0	.	0	.	1076	18
	51-60 cm	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	115	84	0	.	0	.	0	.	0	.	27	71	20	72	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	13	100	14	100	62	60	63	67	28	73	41	100	146	47	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	56	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	25	100	0	.	0	.	0	.	612	25
	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	.	24	.	15	100	20	100	18	100	19	72	19	100	17	100	20	100	58	59	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	.	238	29
	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	.	30	100	18	100	0	.	0	.	55	72	19	100	0	.	75	61	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	27	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	224	34
	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	.	82	100	28	100	0	.	0	.	28	100	26	100	0	.	61	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	.	226	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	.	0	.	0	.	0	.	0	.	69	71	0	.	0	.	11	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	.	80	63
	>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	.	50	100	0	.	0	.	0	.	0	.	242	85	0	.	192	58	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	485	49
	total	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	709	45	0	.	0	.	0	.	0	.	665	39	106	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	.	82	.	62	.	322	65	247	79	550	36	1057	30	2239	19	702	40	354	39	1795	27	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	134	72	0	.	0	.	63	.	0	.	0	.	0	.	602	40	283	50	165	58	0	.	0	.	0	.	0	.	0	.	258	74	0	.	0	.	0	.	10394	9
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	302	24	415	39	239	54	244	29	86	53	258	34	1213	16	1099	15	1262	17	986	18	91	57	214	44	237	34	5	.	254	43	553	28	587	27	335	32	217	49	361	27	414	25	387	28	302	24	844	15	861	17	1024	19	360	29	521	26	608	18	118	52	240	28	105	40	101	42	247	37	224	41	254	33	295	27	185	33	291	31	255	34	230	33	312	26	476	23	158	36	227	36	242	40	184	29	211	40	309	34	167	40	183	45	244	38	546	39	86	41	183	39	157	30	413	32	466	25	810	20	515	31	350	28	471	24	247	37	105	46	290	39	180	30	93	65	191	41	108	45	105	56	284	29	102	50	41	36	228	30	198	37	242	39	159	41	174	43	119	59	17	71	90	48	913	18	669	17	764	18	176	39	83	41	115	36	414	42	247	41	236	43	110	49	130	43	0	.	30362	3
	21-30 cm	539	28	429	32	229	41	659	25	430	33	933	28	2945	12	2441	14	3009	13	2306	16	153	52	384	34	482	31	26	.	230	45	945	25	1160	25	850	25	255	49	931	34	916	18	697	23	754	21	2183	15	1971	16	2038	15	584	29	916	24	1422	22	198	39	492	30	294	33	234	42	415	31	555	31	320	42	680	27	604	28	586	31	786	23	412	37	1114	27	787	25	292	37	486	30	288	34	680	29	251	34	618	31	368	31	693	30	416	33	435	37	61	43	323	30	352	28	296	29	644	23	741	22	535	25	494	29	627	28	341	36	224	57	451	39	222	37	304	42	375	45	332	43	78	86	637	29	170	53	172	48	498	26	366	29	527	31	325	36	234	36	339	44	91	61	215	56	1298	15	1266	17	1480	16	193	42	188	42	292	37	770	28	718	26	233	35	282	37	153	40	0	.	59671	2
	31-40 cm	1183	23	577	30	551	36	1444	20	720	30	1279	27	4324	12	3858	13	4053	12	2942	16	251	43	483	40	694	28	46	.	516	38	1061	29	1600	23	1536	26	51	87	1292	29	1528	21	870	23	1205	22	2710	15	2927	14	3561	15	1497	26	1914	19	1733	21	315	39	467	37	368	38	302	40	809	32	608	34	389	34	1142	24	969	26	769	31	731	23	526	30	1316	25	1373	22	320	41	869	32	607	32	948	26	548	31	859	26	739	30	540	30	371	33	687	28	164	42	467	27	546	35	151	36	337	32	559	27	385	26	280	34	644	31	352	32	271	57	662	32	359	44	544	44	356	39	377	40	251	85	737	26	438	51	309	40	437	27	527	31	665	29	673	29	355	49	245	48	131	54	535	54	1874	17	1392	18	1815	17	309	36	305	36	796	33	1053	25	965	23	541	31	632	39	435	39	0	.	84848	2
	41-50 cm	1153	23	1035	30	253	40	2217	22	679	32	1583	25	5725	13	4838	12	5369	11	2317	16	343	50	217	45	605	33	16	.	401	44	1248	26	1341	22	1615	25	70	85	1191	22	1740	19	1080	21	1955	19	3193	14	2767	13	2996	14	1414	28	2055	21	2195	20	380	33	555	30	428	36	252	40	882	25	359	39	531	37	1301	28	872	31	638	32	990	26	685	32	1778	25	971	25	1017	29	663	34	1059	32	752	30	588	27	1371	29	569	30	917	34	829	34	607	25	225	41	493	28	614	28	154	46	139	40	266	32	305	30	287	40	372	30	243	46	296	48	391	35	580	37	427	39	381	31	487	41	160	68	567	29	240	49	263	49	447	24	372	38	569	43	789	30	375	49	334	41	141	51	526	47	1707	17	1591	19	1670	16	431	39	693	33	841	29	1258	27	962	27	823	31	553	33	722	34	0	.	92298	2
	51-60 cm	1060	28	899	30	275	40	1178	23	413	44	781	30	4444	12	4219	14	4398	14	1177	20	485	43	84	51	464	34	0	.	274	46	461	37	1083	28	755	28	115	84	762	27	1342	24	1096	22	1289	20	2292	15	2113	17	1988	16	1195	29	1404	22	1734	23	227	44	308	41	263	52	233	59	775	30	354	41	296	37	952	33	630	34	389	42	837	34	578	34	1407	23	770	23	745	40	196	44	424	43	287	37	527	32	702	30	463	37	462	37	447	39	604	31	299	44	452	27	331	33	96	45	128	43	109	57	284	39	139	46	373	36	375	48	194	48	289	43	452	40	255	41	349	47	314	50	0	.	606	39	59	62	289	51	347	30	430	42	292	48	476	37	135	68	245	47	139	67	367	49	1179	21	902	22	1470	20	251	41	451	35	591	34	801	29	797	32	458	35	514	54	383	41	0	.	66283	3
	61-70 cm	400	43	287	41	172	53	606	34	181	60	96	59	1542	18	2219	17	1902	19	292	38	239	50	152	78	136	59	0	.	75	73	288	42	741	34	115	53	0	.	537	40	860	23	393	34	663	28	1206	20	437	27	836	27	483	49	640	26	530	38	55	71	116	50	95	58	151	50	302	36	15	100	246	43	354	44	208	46	356	58	413	38	499	36	634	39	255	46	383	44	70	70	174	52	52	100	379	43	207	45	400	48	180	52	225	53	449	39	295	49	286	51	176	55	100	45	83	78	19	100	172	38	101	51	129	49	103	50	130	85	88	75	278	36	131	55	46	72	349	44	0	.	154	56	69	70	160	65	29	100	142	64	72	71	89	58	0	.	196	69	45	100	82	76	798	30	290	32	608	26	66	71	65	71	248	45	277	42	182	54	175	45	82	59	202	56	0	.	28760	4
	71-80 cm	128	72	217	60	69	71	237	51	127	76	0	.	431	31	816	25	989	28	212	52	168	77	0	.	50	100	0	.	0	.	90	100	122	50	66	71	0	.	344	35	300	39	294	50	344	33	905	28	321	34	234	41	0	.	113	71	124	71	77	71	109	72	32	100	121	75	52	100	0	.	0	.	29	100	88	71	122	76	94	59	360	48	334	54	0	.	69	71	81	71	45	100	0	.	122	58	56	100	110	60	146	50	54	100	258	49	37	100	166	53	163	58	26	100	20	100	55	72	104	53	0	.	136	47	89	58	42	100	59	71	28	100	76	71	0	.	102	71	0	.	33	100	82	71	0	.	95	71	0	.	0	.	0	.	0	.	90	72	115	100	27	100	695	28	164	49	216	45	42	100	130	72	28	100	102	61	108	71	0	.	36	100	0	.	0	.	12128	7
	81-90 cm	0	.	33	100	0	.	53	100	0	.	0	.	167	51	581	32	382	42	49	100	0	.	62	100	0	.	0	.	0	.	107	71	0	.	123	100	0	.	106	59	50	100	26	100	127	52	88	72	110	58	49	100	137	77	0	.	0	.	0	.	0	.	60	100	0	.	53	100	0	.	0	.	0	.	0	.	50	100	42	100	0	.	53	100	0	.	0	.	0	.	0	.	0	.	53	100	0	.	37	100	58	100	99	100	0	.	27	100	82	100	28	100	0	.	0	.	28	100	99	78	0	0	61	71	0	.	0	.	45	100	119	81	57	100	37	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	48	100	0	.	0	.	177	45	109	72	65	72	0	.	0	.	0	.	56	100	0	.	91	71	43	100	0	.	0	.	3926	12
	91-100 cm	0	.	0	.	0	.	67	100	0	.	0	.	0	.	75	100	73	100	57	100	87	100	0	.	0	.	0	.	0	.	0	.	0	.	72	100	0	.	86	71	0	.	0	.	61	100	0	.	0	.	57	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	80	100	0	.	116	72	0	0	63	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	124	71	0	.	0	.	81	100	60	100	85	100	0	.	0	.	41	100	69	71	0	.	0	.	11	100	0	.	37	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	83	71	39	100	48	100	0	.	60	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	1633	19
	>100 cm	0	.	0	.	0	.	0	.	0	.	0	.	55	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	56	100	183	61	51	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	.	69	100	50	100	0	.	0	.	0	.	0	.	338	67	0	.	192	58	0	.	0	.	0	.	0	.	44	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	37	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	1075	29
	total	4766	19	3891	23	1787	30	6705	18	2635	28	4929	22	20845	10	20147	10	21437	9	10339	12	1817	34	1596	32	2668	26	92	.	1749	33	4753	21	6634	19	5468	21	709	45	5610	20	7150	15	4844	17	6754	16	13603	11	11559	11	12783	11	5669	21	7562	17	8345	17	1370	34	2286	24	1644	31	1396	34	3536	22	2115	28	2036	29	4753	23	3635	23	3201	28	4262	20	3292	26	7011	20	4633	18	2985	26	2592	25	2840	27	2903	23	2677	24	4123	23	2975	25	3179	25	2684	27	3668	22	1324	30	2588	22	2367	25	1236	24	1857	23	2657	17	2738	20	1650	23	3016	21	1751	29	1299	41	2273	29	2218	27	1933	31	1736	31	2070	34	594	66	3019	23	1160	41	1234	37	2080	21	2034	29	2367	25	2511	24	1273	35	1616	38	678	55	1841	43	8760	12	6423	14	8138	13	1468	31	1975	29	2912	27	4730	21	3979	20	2557	26	2252	31	2025	29	0	.	380985	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. 2300807. Birmensdorf, Swiss Federal Research Institute WSL

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