Selection from the list of topics

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

1. What do the numbers stand for?

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

Example 1: Estimated value and standard error

NFI5

volume of deadwood (stemwood)
ownership (2 categories)

regional demarcation: production region

unit: m³/ha

evaluation area: accessible forest without shrub forest

grid: 1.4 km grid, subgrids 1-5

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

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

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2. What is the purpose of the standard error?

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

The statistical certainty is:

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

Example 2: Calculating confidence intervals

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

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

Procedure

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

Answer

			Step 1	Step 2

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

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

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

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

Data: see example 2

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

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

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3. When are two results statistically different?*

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

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

Example 4: Interpretation of two results from the same inventory

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

	case 2						case 1

case 1

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

Procedure

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

Answer

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

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

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

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

Case 2

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

Procedure

See case 1.

Answer

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

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

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

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

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

Example 5: Interpretation of two results from different inventories

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

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

Procedure

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

Answer

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

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

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

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

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

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

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

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

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

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

Procedure

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

Answer

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

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

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

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

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

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

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

Procedure

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

Answer

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

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

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

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

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

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

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

Example 8: Standard error and combination of variable expressions

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

The standard error increases as the level of detail increases.

Large standard errors are to be expected if:

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

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

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

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5. Two types of changes?

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

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

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

The results are:

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

Example 9: : Additivity/non-additivity of changes

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

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

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

Example 10: Average number of years per domain

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

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

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

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

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

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

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

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

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

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

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NFI3
growing stock (stemwood)
altitudinal vegetation belts (NaiS; 6 classes) · diameter at breast height (10 classes)
regional demarcation: forest district (2024)
unit: 1000 m³
evaluation area: accessible forest without shrub forest NFI1-NFI5
grid: 1.4 km grid, subgrids 1-5
state 2004/06
		forest district (2024)
		AG01		AG02		AG03		AG04		AI01		AR01		BE01		BE02		BE03		BE04		BSBL01		BSBL02		BSBL03		BSBL04		FR01		FR02		FR03		FR04		GE01		GL01		GR01		GR02		GR03		GR04		GR05		JU01		LU01		LU02		LU03		NE01		NE02		NE03		NE04		NE06		NW01		OW01		OW02		SG01		SG02		SG03		SG04		SG05		SH01		SO01		SO02		SO03		SO04		SZ01		SZ02		SZ03		TG01		TG02		TG03		TI01		TI02		TI03		TI04		TI05		TI06		TI07		TI08		TI09		UR01		UR02		UR03		VD02		VD03		VD04		VD05		VD06		VD07		VD08		VD09		VD11		VD12		VD14		VD15		VD16		VD18		VD20		VD22		VS01		VS02		VS03		ZG01		ZH01		ZH02		ZH03		ZH04		ZH05		ZH06		ZH07		lakes		Switzerland
altitudinal vegetation belts (NaiS; 6 classes)	diameter at breast height (10 classes)	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%
n/a	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	12-20 cm	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	21-30 cm	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	31-40 cm	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	41-50 cm	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	51-60 cm	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	61-70 cm	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	71-80 cm	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	81-90 cm	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	91-100 cm	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	>100 cm	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	total	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.
upper subalpine	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	12-20 cm	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	1	.	10	51	234	25	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	8	100	16	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	.	157	58	59	48	7	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	492	23
	21-30 cm	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	24	.	0	.	19	.	27	58	437	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	.	31	89	34	78	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	221	44	52	48	26	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	871	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	.	11	.	83	52	532	28	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	-15	100	23	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	.	191	31	207	56	18	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	1066	19
	41-50 cm	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	11	.	0	.	0	.	85	46	566	25	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	34	75	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	.	322	34	54	51	7	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	1087	17
	51-60 cm	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	26	.	0	.	0	.	128	54	540	32	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	14	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	109	50	46	58	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	863	23
	61-70 cm	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	54	.	0	.	0	.	19	100	84	60	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	86	51	52	75	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	296	32
	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	.	28	100	242	46	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	115	47	26	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	412	31
	81-90 cm	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	68	72	62	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	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	.	0	.	0	.	0	.	0	.	0	.	0	.	160	53
	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	.	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	.	0	.	0	.	0	.	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	.	84	71
	>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	50	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	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	.	119	59
	total	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	132	.	0	.	31	.	485	46	2795	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	.	57	72	93	74	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	1302	27	496	42	59	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	5449	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	.	207	28	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	20	100	146	42	30	55	50	38	172	31	223	36	0	.	0	.	0	.	10	.	0	.	0	.	0	.	0	.	0	.	53	94	29	76	57	90	0	.	0	.	8	80	0	.	22	.	0	.	0	.	0	.	0	.	0	.	7	100	0	.	0	.	0	.	0	.	0	.	4	53	45	52	46	54	0	.	0	.	0	.	34	58	11	100	0	.	0	.	6	76	31	100	0	.	4	71	2	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	8	.	0	.	0	.	0	.	0	.	177	25	161	38	106	35	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	1667	11
	21-30 cm	0	.	0	.	0	.	0	.	0	.	0	.	537	23	6	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	14	100	226	34	117	54	222	37	412	31	718	24	0	.	0	.	0	.	10	.	0	.	0	.	0	.	0	.	0	.	96	98	48	100	107	66	0	.	0	.	99	82	0	.	24	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	168	45	45	50	20	.	0	.	0	.	82	59	7	100	0	.	10	.	51	75	20	71	54	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	4	.	0	.	0	.	0	.	0	.	365	38	453	32	200	35	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	4114	9
	31-40 cm	0	.	0	.	0	.	0	.	0	.	0	.	964	23	47	103	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	8	100	405	29	141	79	434	42	682	32	955	24	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	41	74	33	71	169	75	0	.	0	.	50	63	0	.	-3	.	0	.	0	.	0	.	0	.	0	.	80	78	0	.	0	.	0	.	0	.	0	.	42	81	308	40	90	52	6	.	0	.	0	.	71	44	11	74	0	.	0	.	47	83	11	100	33	.	42	74	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	34	.	0	.	0	.	0	.	0	.	494	29	434	29	426	38	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	6056	9
	41-50 cm	0	.	0	.	0	.	0	.	0	.	0	.	938	25	30	71	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	44	82	568	28	171	44	768	31	683	34	1358	20	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	12	100	79	68	122	80	0	.	12	.	123	83	0	.	0	.	0	.	0	.	0	.	0	.	0	.	52	100	0	.	0	.	0	.	0	.	0	.	74	65	256	39	110	66	0	.	0	.	0	.	129	64	33	73	0	.	0	.	66	100	24	100	0	.	41	75	35	70	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	41	.	0	.	0	.	0	.	0	.	706	29	577	32	472	34	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	7525	8
	51-60 cm	0	.	0	.	0	.	0	.	0	.	0	.	629	27	53	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	73	74	557	35	90	64	544	30	450	32	1010	21	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	53	100	17	100	46	100	0	.	43	.	34	71	0	.	0	.	0	.	0	.	0	.	0	.	0	.	73	76	0	.	0	.	0	.	0	.	0	.	146	61	311	39	79	59	0	.	0	.	0	.	97	55	24	100	0	.	29	.	103	72	22	100	34	.	13	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	37	.	0	.	0	.	0	.	0	.	693	28	501	39	533	34	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	6296	9
	61-70 cm	0	.	0	.	0	.	0	.	0	.	0	.	227	45	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	20	100	372	36	40	75	323	42	180	39	506	32	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	41	100	0	.	0	.	0	.	0	.	26	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	59	100	0	.	0	.	0	.	0	.	0	.	43	72	92	65	41	70	0	.	0	.	0	.	78	73	0	0	0	.	0	.	24	100	0	.	104	.	45	72	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	12	.	0	.	0	.	0	.	0	.	701	35	94	50	191	52	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	3218	13
	71-80 cm	0	.	0	.	0	.	0	.	0	.	0	.	155	52	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	41	100	267	54	0	.	131	53	65	73	152	53	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	25	.	26	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	38	100	0	.	0	.	0	.	0	.	0	.	37	100	32	100	0	.	0	.	0	.	0	.	59	71	19	100	0	.	33	.	0	.	0	.	0	.	0	.	32	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	419	39	27	100	113	74	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	1671	17
	81-90 cm	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	62	72	120	71	41	100	58	100	0	.	57	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	.	46	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	345	40	33	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	761	26
	91-100 cm	0	.	0	.	0	.	0	.	0	.	0	.	33	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	99	74	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	0	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	133	61
	>100 cm	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	52	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	45	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	97	71
	total	0	.	0	.	0	.	0	.	0	.	0	.	3689	21	136	88	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	281	67	2661	26	630	46	2682	26	2645	25	4978	18	0	.	0	.	0	.	20	.	0	.	0	.	0	.	0	.	0	.	296	72	206	65	501	64	0	.	80	.	411	63	0	.	43	.	0	.	0	.	0	.	0	.	0	.	310	71	0	.	0	.	0	.	0	.	0	.	347	60	1211	33	412	49	26	.	0	.	0	.	550	46	105	71	0	.	71	.	298	73	108	74	224	.	146	64	114	85	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	135	.	0	.	0	.	0	.	0	.	3900	22	2279	26	2040	28	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	31536	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	.	278	22	7	76	0	.	4	100	0	.	0	.	0	.	0	.	7	.	83	68	5	72	7	77	0	.	28	65	69	38	198	34	387	28	605	20	311	25	0	.	17	.	0	.	82	52	0	.	0	.	0	.	0	.	0	.	6	.	124	39	3	71	0	.	18	100	11	64	4	.	0	0	0	.	0	.	0	.	0	.	0	.	-3	420	49	60	10	71	0	.	0	.	0	.	141	48	72	52	54	47	4	71	0	.	0	.	22	54	20	70	46	87	10	109	19	72	114	45	45	81	41	43	53	68	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	11	84	0	.	0	.	0	.	0	.	429	25	527	26	264	26	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	4179	7
	21-30 cm	0	.	0	.	0	.	0	.	0	.	0	.	630	21	17	79	0	.	0	.	0	.	0	.	0	.	0	.	27	.	224	62	18	71	35	71	0	.	89	80	230	38	359	42	388	27	1043	20	830	24	0	.	36	.	0	.	205	65	0	.	0	.	0	.	0	.	0	.	8	.	316	47	62	56	0	.	24	100	25	83	5	.	0	0	0	.	0	.	0	.	0	.	0	.	25	85	73	99	11	100	0	.	0	.	0	.	68	50	81	59	163	40	26	73	0	.	0	.	104	53	64	64	14	166	41	89	80	85	341	38	59	60	33	61	152	95	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	61	100	0	.	0	.	0	.	0	.	722	23	844	26	753	29	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	8289	7
	31-40 cm	0	.	0	.	0	.	0	.	0	.	0	.	754	24	149	68	0	.	17	100	0	.	0	.	0	.	0	.	29	.	185	67	6	215	43	75	0	.	44	73	660	34	332	32	396	28	2009	18	1416	25	0	.	15	.	0	.	95	53	0	.	0	.	0	.	0	.	0	.	39	.	179	45	162	61	0	.	56	100	29	61	49	.	0	.	0	.	0	.	0	.	0	.	0	.	174	51	72	120	53	72	0	.	0	.	0	.	54	87	65	61	298	48	35	73	0	.	0	.	159	55	105	74	106	70	99	68	171	95	446	45	62	74	284	69	117	59	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	50	100	0	.	0	.	0	.	0	.	915	26	725	25	667	28	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	11323	7
	41-50 cm	0	.	0	.	0	.	0	.	0	.	0	.	1351	22	177	55	0	.	0	.	0	.	0	.	0	.	0	.	78	.	236	68	93	84	99	71	0	.	120	75	1006	41	262	38	793	27	2034	17	1395	21	0	.	24	.	0	.	233	53	0	.	0	.	0	.	0	.	0	.	8	.	164	49	94	53	0	.	62	100	0	0	59	.	100	100	0	.	0	.	0	.	0	.	0	.	110	62	72	82	73	78	0	.	0	.	0	.	48	62	132	66	616	37	35	100	0	.	0	.	56	61	56	82	83	73	115	58	155	89	298	45	191	87	277	53	134	66	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	125	82	0	.	0	.	0	.	0	.	570	28	1228	23	855	25	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	13618	7
	51-60 cm	0	.	0	.	0	.	0	.	0	.	0	.	1860	23	61	100	0	.	10	100	0	.	0	.	0	.	0	.	25	.	34	83	104	74	34	71	0	.	122	62	607	33	332	41	1027	26	1934	20	832	29	0	.	-5	.	0	.	157	59	0	.	0	.	0	.	0	.	0	.	0	.	169	59	183	53	0	.	0	.	15	100	17	.	46	100	0	.	0	.	0	.	0	.	0	.	139	66	51	100	50	100	0	.	0	.	0	.	108	53	69	58	328	45	49	75	0	.	0	.	20	100	91	76	136	79	71	75	65	100	246	48	297	56	204	58	131	54	0	.	0	.	37	100	0	.	0	.	0	.	0	.	0	.	22	100	0	.	0	.	0	.	0	.	557	32	579	26	977	29	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	11790	7
	61-70 cm	0	.	0	.	0	.	0	.	0	.	0	.	887	30	24	100	0	.	0	.	0	.	0	.	0	.	0	.	31	.	0	.	0	0	91	81	0	.	141	67	441	51	114	66	588	31	756	26	123	50	0	.	0	.	0	.	47	71	0	.	0	.	0	.	0	.	0	.	0	.	82	58	42	72	0	.	0	0	0	0	14	.	32	100	0	.	0	.	0	.	0	.	0	.	92	66	0	.	0	.	0	.	0	.	0	.	200	60	133	61	240	49	46	70	0	.	0	.	25	100	22	100	125	84	22	100	0	0	56	71	87	75	88	73	146	100	0	.	0	.	35	100	0	.	0	.	0	.	0	.	0	.	50	100	0	.	0	.	0	.	0	.	267	54	386	32	378	35	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	5810	10
	71-80 cm	0	.	0	.	0	.	0	.	0	.	0	.	350	32	0	.	0	.	41	100	0	.	0	.	0	.	0	.	0	.	0	.	96	100	0	.	0	.	246	65	143	51	33	100	153	51	799	34	192	43	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	77	100	52	71	0	.	0	.	59	100	0	.	65	100	0	.	0	.	0	.	0	.	0	.	52	74	0	.	37	100	0	.	0	.	0	.	80	70	130	80	109	58	0	0	0	.	0	.	0	0	41	100	49	100	64	72	0	.	46	100	0	0	0	0	0	.	0	.	0	.	44	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	339	44	121	50	256	46	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	3675	13
	81-90 cm	0	.	0	.	0	.	0	.	0	.	0	.	170	58	0	.	0	.	99	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	89	71	39	100	51	100	141	59	356	42	66	82	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	57	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	40	100	44	100	46	100	0	.	0	.	0	.	73	100	0	.	0	.	0	.	0	.	0	.	31	100	50	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	186	67	80	71	33	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	1652	19
	91-100 cm	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	113	71	0	.	0	.	53	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	.	77	100	0	.	0	.	0	.	47	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	92	71	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	382	38
	>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	.	160	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	.	134	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	.	48	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	380	49
	total	0	.	0	.	0	.	0	.	0	.	0	.	6281	18	436	57	0	.	171	92	0	.	0	.	0	.	0	.	196	.	762	55	323	70	309	71	0	.	992	55	3194	29	1682	29	3925	21	9697	14	5165	18	0	.	87	.	0	.	819	46	0	.	0	.	0	.	0	.	0	.	62	.	1112	41	599	47	0	.	161	100	195	66	149	.	243	100	0	.	0	.	0	.	0	.	0	.	587	47	317	73	234	71	0	.	0	.	0	.	872	38	726	50	1854	32	195	70	0	.	0	.	536	50	399	57	559	67	422	60	537	76	1547	38	772	56	1015	47	732	60	0	.	0	.	117	100	0	.	0	.	0	.	0	.	0	.	320	59	0	.	0	.	0	.	0	.	3984	19	4583	19	4230	20	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	61096	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	112	73	3	.	0	.	30	61	54	75	201	39	703	29	642	18	174	45	715	17	0	.	19	61	74	41	0	.	44	61	127	37	370	29	95	46	0	.	360	28	86	55	102	33	21	62	109	40	0	.	665	23	200	32	115	28	476	22	29	48	221	26	28	73	83	39	228	30	194	42	53	61	181	35	111	48	141	46	170	35	104	58	181	42	157	56	118	38	127	38	79	57	87	40	133	42	198	33	149	40	185	47	0	.	84	67	0	.	43	55	0	.	188	41	170	41	95	43	247	33	270	41	59	58	120	45	27	140	30	84	88	44	25	61	89	48	51	48	0	.	179	28	6	.	37	65	211	28	92	67	151	43	26	58	82	80	79	64	17	71	13	100	0	.	9	.	259	25	127	50	65	52	10	67	85	99	112	77	0	.	37	.	4	.	0	.	11638	5
	21-30 cm	40	63	6	.	0	.	90	53	323	39	733	30	956	19	1531	16	504	27	2111	17	10	100	71	61	216	48	0	.	202	61	287	37	671	26	329	50	0	.	1190	37	368	34	160	34	23	66	186	37	0	.	958	19	259	34	569	35	1267	23	175	62	463	34	119	53	176	43	298	33	519	35	33	85	542	31	479	34	358	38	553	28	341	51	815	27	437	44	198	45	323	39	86	59	290	41	245	41	474	36	209	41	454	43	0	.	88	56	0	.	178	56	0	.	187	43	308	48	116	59	438	36	415	40	129	41	307	45	76	76	23	77	111	52	92	50	294	47	240	52	0	.	523	28	63	.	92	50	505	27	144	40	345	44	67	51	130	61	107	71	58	71	29	100	0	.	10	.	501	29	169	41	120	53	24	71	538	32	315	37	0	.	58	.	16	.	0	.	27466	4
	31-40 cm	139	51	0	.	0	.	80	57	769	31	1221	26	1672	19	2290	17	888	33	2405	15	65	100	111	65	267	48	0	.	138	64	610	32	1029	28	410	34	0	.	1116	30	343	35	432	29	26	75	261	44	0	.	2133	19	480	35	553	32	1297	24	147	52	535	32	170	48	223	41	705	26	621	36	79	58	521	32	773	28	457	38	708	29	564	33	1189	24	496	35	328	50	499	31	48	67	555	35	304	38	550	30	551	35	457	37	0	.	132	68	0	.	45	82	0	.	71	80	151	52	102	58	208	36	167	43	158	44	287	46	101	86	119	65	227	50	83	52	338	40	121	50	11	.	623	27	36	.	154	59	620	25	221	48	512	32	131	63	171	56	233	54	155	52	25	100	0	.	0	.	568	27	184	46	380	43	116	55	793	28	657	34	0	.	147	.	0	.	0	.	37261	3
	41-50 cm	198	59	15	.	0	.	335	44	798	30	1438	25	2014	20	3047	14	1637	23	2845	15	72	100	58	100	345	49	0	.	111	68	394	36	932	28	676	40	0	.	1426	29	371	40	641	31	69	62	43	57	0	.	2241	17	488	31	714	32	2153	21	209	47	634	30	230	53	259	43	822	29	322	36	78	47	835	31	1028	30	399	47	717	31	473	51	1413	27	262	49	356	38	373	36	238	58	557	33	553	32	885	30	509	35	388	43	0	.	129	63	0	.	150	50	0	.	54	73	133	38	90	57	257	41	190	46	182	45	99	60	74	54	113	75	261	48	72	61	333	43	267	56	76	.	653	25	51	.	173	58	545	24	329	40	439	32	176	42	234	82	211	52	168	61	45	71	0	.	0	.	596	29	299	46	243	42	193	59	891	27	774	30	0	.	72	.	46	.	0	.	43220	3
	51-60 cm	118	69	0	.	0	.	275	56	792	32	1169	28	1782	22	3106	15	1167	25	1365	19	0	.	0	.	404	48	0	.	24	100	496	35	760	29	594	38	0	.	1101	27	179	58	590	34	54	74	151	63	0	.	1280	20	424	40	828	29	1405	26	120	54	549	35	203	57	294	47	737	26	305	47	34	100	575	36	426	38	158	47	691	37	822	34	1432	22	179	53	437	40	225	55	235	52	375	49	403	37	878	33	463	40	332	49	0	.	73	74	0	.	282	53	0	.	124	53	91	62	64	100	107	42	120	58	122	46	178	59	83	68	67	85	306	53	170	72	383	53	406	51	0	.	527	35	45	.	222	57	388	28	248	43	351	42	405	51	100	100	209	52	198	59	192	80	0	.	0	.	381	35	142	52	442	49	204	58	842	32	409	41	0	.	20	.	57	.	0	.	35893	4
	61-70 cm	46	100	0	.	0	.	52	71	205	42	593	30	779	30	1828	18	783	28	580	25	0	.	70	100	81	73	0	.	0	.	249	53	373	48	156	54	0	.	169	41	114	51	488	31	14	100	63	71	0	.	674	31	599	43	520	37	675	32	63	72	212	40	100	100	110	76	483	35	88	58	36	100	549	44	477	43	267	71	393	42	152	46	1183	30	28	100	182	61	65	72	30	100	112	82	292	47	319	41	308	53	26	100	0	.	171	61	0	.	40	100	0	.	40	71	55	71	0	.	146	43	0	.	61	71	191	62	24	100	69	71	186	63	180	63	122	64	226	67	0	.	294	58	0	.	143	61	59	71	371	57	107	58	79	66	0	.	147	65	35	100	166	100	0	.	0	.	75	61	133	62	270	62	109	83	370	40	61	71	0	.	0	.	26	.	0	.	18543	6
	71-80 cm	0	.	0	.	0	.	0	.	124	77	0	.	248	47	1268	22	455	41	130	76	0	.	0	.	0	.	0	.	0	.	86	71	194	64	39	100	0	.	341	44	101	72	208	54	110	72	105	60	0	.	411	37	129	74	187	63	275	48	108	73	70	71	29	100	205	59	186	50	0	.	0	.	109	71	136	58	0	.	204	63	437	50	320	48	0	.	45	100	52	100	51	100	0	.	212	53	134	74	153	73	101	72	0	.	93	100	0	.	0	.	0	.	0	.	53	73	0	.	67	74	0	.	40	71	0	.	85	100	80	100	81	71	0	.	26	100	130	59	0	.	79	71	0	.	0	.	89	71	0	.	0	.	88	72	0	.	153	100	119	100	38	100	0	.	0	.	45	71	0	.	108	72	44	100	0	.	163	50	0	.	0	.	0	.	0	.	8545	8
	81-90 cm	0	.	0	.	0	.	63	100	49	100	0	.	109	71	556	35	187	58	57	100	0	.	0	.	0	.	0	.	0	.	57	100	53	100	0	.	0	.	20	100	0	.	0	.	0	.	38	100	0	.	47	100	0	.	0	.	0	.	45	100	121	71	67	100	0	.	115	70	0	.	0	.	0	.	58	100	0	.	0	.	115	73	318	88	0	.	0	.	0	.	0	.	0	.	112	71	0	.	110	71	0	.	0	.	0	.	0	.	67	100	0	.	21	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	47	100	64	100	0	0	0	.	0	.	0	.	0	.	0	.	0	.	60	100	0	.	0	.	0	.	0	.	50	100	71	100	0	.	0	.	0	.	57	73	53	100	38	100	44	100	44	100	0	.	0	.	0	.	0	.	0	.	2912	16
	91-100 cm	0	.	54	.	0	.	60	100	0	.	0	.	0	.	0	.	61	100	0	0	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	0	0	.	0	.	0	.	57	100	0	.	68	100	45	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	0	70	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	82	100	0	.	0	.	0	.	0	.	91	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	.	587	34
	>100 cm	0	.	0	.	0	.	0	.	0	.	0	.	0	.	91	100	0	.	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	.	0	.	0	.	0	.	0	.	91	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	.	244	59
	total	654	48	78	.	0	.	985	43	3114	28	5355	22	8263	16	14360	12	5854	20	10208	12	147	100	329	57	1388	40	0	.	519	55	2305	30	4382	21	2300	31	0	.	5724	24	1563	29	2621	25	317	56	1012	37	0	.	8537	15	2625	28	3486	26	7549	19	896	42	2805	24	946	43	1349	36	3575	22	2049	30	313	53	3312	28	3578	25	1779	35	3435	23	3007	29	6922	21	1559	35	1664	32	1663	28	767	45	1976	33	2253	29	3438	25	2534	30	1943	32	0	.	770	55	0	.	895	46	0	.	685	36	962	35	467	39	1470	28	1163	34	753	36	1182	36	471	53	548	60	1324	36	621	52	1585	36	1441	44	87	.	2877	23	201	.	821	48	2476	20	1405	35	1906	27	971	40	718	56	1189	49	821	55	508	74	0	.	19	.	2481	24	1107	37	1666	36	742	48	3563	23	2492	27	0	.	334	.	149	.	0	.	186309	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	242	34	233	39	195	48	190	36	0	.	0	.	48	46	165	34	847	17	73	.	93	63	61	58	98	43	0	.	31	50	155	42	0	.	108	40	0	.	0	.	37	65	37	61	0	.	0	.	0	.	209	29	100	50	302	30	2	583	27	120	0	.	36	57	6	.	0	.	0	.	0	.	47	71	32	90	160	57	30	84	66	58	0	.	359	36	69	57	4	278	72	45	60	46	29	95	0	.	0	0	173	40	209	33	379	38	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	43	80	0	.	4	128	59	57	57	62	0	.	42	69	43	88	1	100	30	71	25	81	0	.	102	62	51	54	84	54	112	54	16	59	0	.	7	100	0	.	0	.	91	53	18	74	54	55	148	51	43	83	60	40	158	47	51	44	140	42	0	.	6427	6
	21-30 cm	391	31	324	38	264	35	472	34	0	.	0	.	193	53	427	33	1868	17	84	.	112	50	234	47	280	40	14	.	116	56	268	41	0	.	266	40	0	.	0	.	68	81	21	181	0	.	0	.	0	.	635	28	269	38	520	31	40	100	24	75	0	.	52	57	13	.	0	.	0	.	0	.	64	100	116	60	198	44	24	90	163	68	0	.	690	29	86	57	129	53	153	42	308	46	28	76	0	.	25	100	262	43	568	32	368	48	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	181	80	0	.	57	73	136	66	88	68	0	.	96	93	90	54	69	72	62	61	40	60	0	.	115	65	110	59	139	59	162	52	121	72	0	.	76	61	0	.	0	.	80	81	37	75	91	67	198	45	151	86	214	38	190	41	245	46	291	37	0	.	13174	6
	31-40 cm	827	46	415	32	372	35	611	29	0	.	0	.	273	47	454	27	2158	15	0	.	190	41	443	39	439	40	50	.	101	60	354	45	0	.	518	34	0	.	0	.	48	66	69	64	0	.	0	.	0	.	771	26	518	45	841	32	94	72	91	59	0	.	188	60	19	.	0	.	0	.	0	.	4	100	72	76	287	58	16	99	107	73	0	.	563	30	157	40	141	47	299	41	347	42	20	71	0	.	132	78	263	51	424	32	450	29	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	84	73	0	.	97	74	150	54	93	80	0	.	116	70	96	61	28	100	110	87	144	84	0	.	56	98	230	54	224	52	167	49	150	78	0	.	62	60	0	.	0	.	16	100	57	71	102	59	385	41	44	72	273	43	243	42	420	46	238	38	0	.	16715	5
	41-50 cm	788	27	682	38	388	45	1061	24	0	.	0	.	573	48	499	40	2943	14	0	.	147	52	275	46	349	53	58	.	315	56	374	43	0	.	442	37	0	.	0	.	114	85	94	63	0	.	0	.	0	.	1067	26	704	53	835	29	60	71	115	71	0	.	179	52	-3	.	0	.	0	.	0	.	15	100	99	90	305	54	39	77	108	69	0	.	985	28	395	43	239	57	348	42	160	62	51	100	0	.	81	73	197	45	655	33	514	33	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	-31	100	0	.	38	92	134	67	99	63	0	.	136	67	23	80	64	82	323	64	82	79	0	.	26	138	146	64	300	45	297	50	84	74	0	.	110	68	0	.	0	.	50	87	87	87	161	58	362	34	0	.	365	39	551	35	459	36	355	39	0	.	20470	5
	51-60 cm	690	30	639	31	238	41	1409	26	0	.	0	.	349	45	604	38	3130	16	0	.	218	40	98	59	181	46	0	.	264	65	219	52	0	.	495	35	0	.	0	.	61	71	84	59	0	.	0	.	0	.	881	26	352	46	887	33	76	72	111	52	0	.	125	82	0	.	0	.	0	.	0	.	22	100	87	100	51	73	53	100	157	62	0	.	576	33	605	47	22	104	208	59	79	61	6	100	0	.	110	80	128	54	687	39	489	36	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	50	100	0	.	0	.	16	100	222	81	0	.	70	78	14	100	77	103	25	100	20	100	0	.	79	61	66	73	166	56	61	71	80	85	0	.	144	70	0	.	0	.	0	.	68	100	301	48	331	38	0	.	409	40	718	40	311	47	436	40	0	.	18056	6
	61-70 cm	449	40	192	45	286	48	604	34	0	.	0	.	194	64	397	48	1483	22	0	.	300	47	150	84	158	67	31	.	65	71	22	100	0	.	30	100	0	.	0	.	22	100	0	.	0	.	0	.	0	.	170	49	287	52	264	55	81	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	47	100	0	.	57	100	0	.	344	51	169	60	0	.	68	71	0	.	25	100	0	.	0	.	25	100	257	49	252	52	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	21	100	0	.	0	.	26	100	31	100	0	.	34	100	0	.	0	.	59	71	0	.	0	.	77	100	0	.	0	.	33	100	30	100	0	.	90	100	0	.	0	.	15	100	34	100	105	58	75	73	0	.	94	77	165	65	101	59	221	58	0	.	7638	9
	71-80 cm	207	59	35	100	77	71	398	43	0	.	0	.	42	100	39	100	551	37	0	.	0	.	0	.	32	100	0	.	0	.	33	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	34	100	0	.	65	100	46	100	0	.	0	.	83	71	0	.	0	.	0	.	0	.	0	.	42	100	35	100	0	.	90	71	0	.	36	100	209	64	0	.	0	.	0	.	0	.	0	.	0	.	0	.	223	52	391	52	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	29	100	0	.	16	100	74	71	0	.	0	.	99	100	0	.	0	.	78	100	0	.	0	.	0	.	35	100	0	.	0	.	24	100	0	.	35	100	0	.	0	.	0	.	0	.	0	.	44	100	0	.	0	.	79	71	71	71	79	71	0	.	3334	14
	81-90 cm	0	.	44	100	46	100	56	100	0	.	0	.	0	.	132	71	99	71	0	.	0	0	63	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	58	100	0	.	0	.	0	.	0	.	0	.	52	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	82	100	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	.	78	100	76	76	45	100	0	.	0	.	877	26
	91-100 cm	42	100	0	.	0	.	71	100	0	.	0	.	0	.	0	.	235	71	0	.	88	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	.	128	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	.	58	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	623	40
	>100 cm	0	.	0	.	0	.	0	.	0	.	0	.	0	.	65	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	73	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	.	138	71
	total	3636	26	2566	23	1867	28	4872	21	0	.	0	.	1673	43	2782	28	13315	12	157	.	1149	35	1324	37	1537	36	153	.	891	48	1426	35	0	.	1933	30	0	.	0	.	351	59	362	55	0	.	0	.	0	.	3766	22	2231	36	3766	25	399	71	368	48	0	.	664	50	35	.	0	.	0	.	0	.	152	84	448	66	1084	43	162	80	829	53	0	.	3552	21	1690	39	535	47	1150	36	954	39	158	76	0	.	347	75	1048	37	3151	27	2888	24	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	376	71	0	.	212	71	595	50	589	55	0	.	594	60	265	52	239	65	685	54	311	71	0	.	456	50	638	49	913	40	832	42	565	68	0	.	524	63	0	.	0	.	253	47	302	79	815	43	1544	30	238	79	1492	32	2181	29	1704	34	1759	29	0	.	87452	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	.	73	55	0	.	0	.	0	.	0	.	177	54	11	83	0	.	0	.	0	.	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	.	14	.	47	110	63	67	271	42	155	49	689	24	168	41	156	60	357	33	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	14	77	0	.	0	.	49	.	0	.	0	.	0	.	118	40	67	51	47	54	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	2567	11
	21-30 cm	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	268	51	0	.	0	.	0	.	0	.	260	49	27	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	.	21	.	37	.	105	55	75	68	169	53	375	32	800	27	132	39	280	58	492	29	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	65	73	0	.	0	.	24	.	0	.	0	.	0	.	143	49	138	55	15	100	0	.	0	.	0	.	0	.	0	.	-1	100	0	.	0	.	0	.	3424	11
	31-40 cm	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	209	53	0	.	0	.	0	.	0	.	184	39	5	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	.	8	.	50	55	71	58	92	46	279	38	489	29	33	71	91	57	307	40	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	47	76	0	.	0	.	6	.	0	.	0	.	0	.	160	52	99	49	64	66	0	.	0	.	0	.	0	.	0	.	87	100	0	.	0	.	0	.	2281	12
	41-50 cm	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	136	83	0	.	0	.	0	.	0	.	71	56	34	78	0	.	0	.	0	.	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	.	7	.	43	45	25	100	8	247	176	36	491	41	48	69	54	74	204	49	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	75	55	58	60	-8	545	0	.	0	.	0	.	0	.	0	.	38	72	0	.	0	.	0	.	1474	18
	51-60 cm	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	45	100	0	.	0	.	0	.	0	.	82	61	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	.	21	.	0	.	20	100	11	100	68	79	70	51	104	67	60	56	14	100	107	69	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	96	85	0	.	26	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	756	22
	61-70 cm	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	29	100	0	.	0	.	0	.	0	.	33	71	13	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	26	.	16	100	0	.	18	100	82	52	71	73	14	100	33	71	45	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	33	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	414	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	.	0	.	22	100	0	.	31	100	12	100	12	100	0	.	49	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	.	126	44
	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	.	44	100	27	100	0	.	0	.	26	100	27	100	0	.	27	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	21	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	171	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	.	68	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	.	150	60
	>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	.	38	100	0	.	0	.	0	.	26	100	193	100	0	.	122	72	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	379	57
	total	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	760	48	0	.	0	.	0	.	0	.	808	38	123	73	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	147	.	92	.	416	49	294	64	625	38	1166	30	2738	19	686	39	628	46	1776	26	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	126	73	0	.	0	.	80	.	0	.	0	.	0	.	592	40	397	49	164	65	0	.	0	.	0	.	0	.	0	.	123	84	0	.	0	.	0	.	11741	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	354	32	236	38	195	48	220	32	54	75	201	39	1236	18	815	16	1021	16	792	18	93	63	80	47	173	30	0	.	81	39	365	27	375	29	210	29	73	55	407	25	338	25	367	22	458	24	1074	16	779	16	873	18	317	26	417	23	570	20	55	63	221	26	64	45	88	37	228	30	253	38	205	30	288	31	142	42	319	36	219	30	174	41	203	39	516	30	187	32	131	38	151	37	148	30	166	38	247	29	159	38	358	31	209	33	554	32	159	44	214	34	178	32	462	29	325	32	784	21	472	23	457	31	462	28	173	38	52	78	179	36	191	33	127	33	143	39	93	41	43	88	181	28	36	62	62	51	211	28	209	42	202	35	129	38	243	41	95	54	17	71	20	74	880	17	823	19	773	15	145	44	119	38	158	48	128	71	172	52	158	47	88	49	144	40	0	.	26969	3
	21-30 cm	431	29	330	37	264	35	562	30	323	39	733	30	2315	12	1981	14	2372	14	2196	17	122	46	305	39	496	31	14	.	345	41	779	27	689	25	631	31	268	51	1292	34	916	19	658	27	653	20	1929	15	2013	14	1592	16	564	25	1089	24	1522	21	199	56	463	34	171	41	189	40	298	33	624	33	398	39	775	25	595	30	580	28	700	26	509	40	839	27	1127	24	284	36	453	31	240	34	598	31	297	35	548	34	245	37	715	31	568	32	477	38	105	47	562	26	316	28	401	31	683	28	916	24	756	24	767	30	635	24	539	38	207	46	441	31	360	34	213	36	445	45	336	46	90	54	592	27	125	59	132	39	505	27	324	32	455	36	271	40	316	37	228	51	58	71	105	52	1450	17	1498	18	1575	17	207	36	211	42	221	41	689	32	529	26	189	41	303	42	307	35	0	.	57339	2
	31-40 cm	966	40	415	32	372	35	690	26	769	31	1221	26	3663	12	2941	14	3045	14	2422	15	255	40	554	34	706	31	50	.	268	41	1149	24	1035	27	971	23	209	53	1168	29	1473	19	975	21	867	25	3220	14	2907	15	2904	15	1013	28	1393	23	1486	22	238	39	535	32	358	39	242	38	705	26	701	32	292	33	855	27	845	26	800	31	803	26	720	29	1186	24	1059	23	485	36	639	26	347	36	903	27	578	27	622	30	735	30	720	30	424	32	582	27	105	56	453	30	481	33	204	37	430	30	591	26	472	25	374	31	571	28	470	34	319	59	673	34	472	32	502	43	455	33	237	43	107	56	651	26	146	70	298	50	620	25	324	38	743	27	440	35	344	37	383	45	155	52	87	51	1760	17	1465	17	1759	17	241	39	482	36	501	34	837	27	930	27	330	40	567	43	238	38	0	.	74702	2
	41-50 cm	986	25	697	37	388	45	1396	21	798	30	1438	25	4877	12	3754	13	4581	12	2845	15	219	48	332	41	694	36	58	.	504	41	1004	27	1026	26	1217	26	136	83	1590	26	2070	23	1168	20	1630	20	2916	14	3354	12	3307	14	1216	33	1549	21	2446	19	325	39	634	30	409	38	256	44	822	29	342	34	322	32	1066	26	1127	28	778	33	879	28	640	41	1514	26	1246	24	750	29	612	31	586	34	717	29	765	26	957	29	663	30	585	32	655	33	657	28	129	44	616	25	758	32	97	58	308	26	581	36	491	29	332	33	469	30	182	52	296	54	473	34	586	39	489	34	502	34	403	43	99	79	717	24	374	57	255	47	545	24	354	38	585	29	640	30	531	45	295	43	168	61	155	52	1672	17	1917	18	1971	16	386	41	404	34	555	30	891	27	1139	24	589	33	531	34	401	36	0	.	87392	2
	51-60 cm	808	27	639	31	238	41	1684	24	792	32	1169	28	4620	13	3824	13	4297	13	1375	19	218	40	98	59	585	36	0	.	312	56	750	28	864	27	1124	25	45	100	1296	24	1431	21	1096	23	1624	19	2746	15	2413	15	2161	16	772	30	1715	22	1638	24	231	37	549	35	328	47	294	47	737	26	358	43	220	48	827	28	513	36	252	37	793	33	996	30	1478	22	754	28	1042	32	247	51	444	39	453	42	621	29	929	32	623	34	460	38	687	39	583	32	254	42	681	29	433	36	241	38	161	41	169	57	283	28	249	41	364	39	328	40	251	45	335	39	653	36	609	40	514	42	476	45	14	100	641	32	70	73	243	53	388	28	328	36	417	37	629	37	161	68	290	45	198	59	335	54	1455	19	1126	22	1918	19	211	48	743	35	535	32	842	32	817	29	718	40	331	45	493	37	0	.	73654	2
	61-70 cm	495	37	192	45	286	48	656	31	205	42	593	30	2087	18	2249	17	2266	17	580	25	300	47	220	65	239	50	31	.	95	58	271	50	373	48	277	42	29	100	331	36	1003	27	642	27	925	25	1052	20	726	25	844	26	886	34	784	31	803	29	63	72	212	40	100	100	110	76	483	35	129	51	118	50	591	41	477	43	313	62	419	40	223	41	1215	29	372	48	351	43	65	72	99	58	112	82	468	35	319	41	308	53	51	71	257	49	424	40	268	47	280	39	282	43	105	44	137	42	71	73	263	33	55	58	231	53	233	52	48	71	125	50	402	42	343	40	267	62	260	60	0	.	329	53	59	71	143	61	59	71	448	50	107	58	141	52	33	100	177	57	35	100	256	74	1054	27	566	25	659	26	168	54	375	47	184	58	370	40	156	54	165	65	101	59	247	53	0	.	35919	4
	71-80 cm	207	59	35	100	77	71	398	43	124	77	0	.	796	23	1306	21	1005	27	170	63	0	.	0	.	32	100	0	.	0	.	118	58	290	54	39	100	0	.	628	36	512	34	241	49	395	33	998	29	586	27	444	35	129	74	252	54	321	44	108	73	70	71	111	58	205	59	186	50	0	.	77	100	161	53	178	50	61	72	288	50	527	43	385	43	36	100	254	55	52	100	51	100	0	.	302	42	134	74	190	62	101	72	223	52	484	46	117	58	162	67	131	51	0	0	84	59	12	100	137	48	60	75	138	49	126	50	85	100	143	66	154	50	0	0	58	71	230	55	0	.	123	58	78	100	0	.	89	71	0	.	35	100	88	72	0	.	177	87	119	100	74	71	873	26	174	41	413	35	0	.	108	72	88	71	0	.	163	50	79	71	71	71	79	71	0	.	17762	6
	81-90 cm	0	.	44	100	46	100	119	71	49	100	0	.	279	45	688	31	286	45	156	73	0	0	63	100	0	.	0	.	0	.	57	100	53	100	0	.	0	.	171	47	159	59	149	58	199	51	461	35	185	54	47	100	0	.	52	100	0	.	45	100	121	71	67	100	0	.	115	70	0	.	0	.	0	.	58	100	0	.	57	100	197	59	318	88	0	.	0	.	0	.	0	.	0	.	112	71	0	.	110	71	0	.	0	.	46	100	40	100	155	59	73	73	21	100	0	.	26	100	99	78	0	.	27	100	0	.	0	.	47	100	96	75	50	100	46	100	0	.	0	.	0	.	0	.	0	.	60	100	0	.	0	.	0	.	0	.	50	100	71	100	0	.	560	34	113	58	111	51	53	100	38	100	44	100	44	100	78	100	76	76	45	100	0	.	0	.	6532	10
	91-100 cm	42	100	54	100	0	.	131	71	0	.	0	.	33	100	0	.	296	60	0	0	88	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	113	71	0	.	0	.	152	59	57	100	47	100	68	100	45	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	0	70	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	82	100	0	.	128	100	0	.	0	.	144	73	0	.	0	.	0	0	29	100	77	100	0	0	68	100	0	.	47	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	58	100	0	.	0	.	37	100	92	71	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	1957	19
	>100 cm	0	.	0	.	0	.	0	.	0	.	0	.	0	.	156	72	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	73	100	0	.	0	.	0	.	0	.	52	100	194	61	50	100	62	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	91	100	0	.	45	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	134	100	38	100	0	.	0	.	0	.	26	100	193	100	0	.	122	72	0	.	0	.	0	.	0	.	38	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	35	100	0	.	48	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	1357	26
	total	4290	23	2644	23	1867	28	5856	19	3114	28	5355	22	19906	10	17714	11	19169	10	10536	12	1296	33	1653	32	2924	27	153	.	1607	34	4493	21	4705	20	4542	20	760	48	6997	22	7901	16	5296	17	6955	15	14647	11	13060	10	12303	12	4942	22	7252	18	8786	17	1264	32	2805	24	1609	32	1384	35	3575	22	2407	27	1632	31	4564	23	4027	24	3103	26	4204	21	3985	24	7207	20	5111	18	3354	25	2199	24	1917	28	2930	25	3309	23	3756	24	3114	26	2991	25	3151	27	3806	22	1310	30	3305	21	2652	25	1531	24	2129	23	3206	17	3243	19	2294	23	3088	21	2051	28	1306	40	2414	28	2914	26	2372	28	2430	30	2035	36	351	46	3233	22	887	48	1132	40	2476	20	1987	28	2544	23	2339	25	1629	33	1754	40	821	55	1032	48	9777	12	7774	14	9227	13	1409	34	2481	28	2286	26	3801	22	3984	20	2304	28	2038	33	1908	27	0	.	383583	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. 2280961. Birmensdorf, Swiss Federal Research Institute WSL

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