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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NFI1
growing stock (stemwood)
altitudinal vegetation belts (NaiS; 6 classes) · diameter at breast height (10 classes)
regional demarcation: forest district (2024)
unit: 1000 m³
evaluation area: accessible forest without shrub forest
grid: 1.4-km grid
state 1983/85
		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	.	5	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	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	.
	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	.	4	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	4	.
	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	.	9	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	9	.
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	.	3	82	3	.	1	.	4	61	228	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	.	8	70	3	73	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	3	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	103	30	29	34	7	80	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	391	14
	21-30 cm	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	36	59	11	.	0	.	37	55	387	20	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	4	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	13	89	19	72	0	.	0	.	0	.	12	100	0	.	0	.	0	.	0	.	21	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	192	31	108	48	39	72	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	879	14
	31-40 cm	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	21	62	12	.	0	.	110	46	600	20	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	4	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	12	85	14	100	0	.	0	.	0	.	15	100	0	.	0	.	0	.	0	.	9	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	315	25	56	61	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	1167	13
	41-50 cm	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	23	84	0	.	0	.	109	38	472	22	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	37	53	7	100	0	.	0	.	0	.	11	100	0	.	0	.	0	.	0	.	5	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	235	23	34	46	13	71	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	944	14
	51-60 cm	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	22	100	17	.	0	.	70	47	374	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	.	18	71	0	.	0	.	0	.	0	.	7	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	113	33	76	44	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	699	17
	61-70 cm	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	14	100	0	.	0	.	68	61	158	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	.	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	.	129	38	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	383	22
	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	.	39	71	99	38	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	12	100	0	.	0	.	0	.	0	.	17	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	58	47	10	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	235	25
	81-90 cm	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	17	100	56	59	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	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	71	22	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	124	38
	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	.	42	71	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	42	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	.	17	100	45	72	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	16	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	78	51
	total	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	117	62	44	.	1	.	471	35	2419	15	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	8	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	100	47	42	73	0	.	0	.	0	.	74	72	0	.	0	.	0	.	0	.	38	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	1234	19	334	34	59	64	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	4941	10
subalpine	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	12-20 cm	0	.	0	.	0	.	0	.	0	.	0	.	171	18	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	13	80	76	30	44	47	116	23	200	23	357	18	0	.	0	.	0	.	13	92	0	.	0	.	0	.	0	.	0	.	36	67	19	95	41	64	0	.	7	100	33	46	0	.	8	.	0	.	0	.	0	.	0	.	0	.	2	71	0	.	0	.	0	.	0	.	0	.	2	76	28	40	18	53	1	.	0	.	0	.	21	47	1	100	5	.	0	.	7	71	8	77	9	77	5	67	15	91	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	3	.	0	.	0	.	0	.	0	.	155	27	184	24	113	25	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	1710	7
	21-30 cm	0	.	0	.	0	.	0	.	0	.	0	.	593	20	23	89	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	50	79	309	28	148	40	324	29	509	23	670	18	0	.	0	.	0	.	10	100	0	.	0	.	0	.	0	.	0	.	25	90	19	66	95	52	0	.	4	100	74	51	0	.	31	.	0	.	0	.	0	.	0	.	0	.	9	80	0	.	0	.	0	.	0	.	0	.	20	61	101	46	40	48	0	.	0	.	0	.	29	50	13	78	11	.	3	.	20	74	19	83	0	100	38	71	34	82	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	4	.	0	.	0	.	0	.	0	.	449	26	441	22	438	28	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	4551	7
	31-40 cm	0	.	0	.	0	.	0	.	0	.	0	.	980	20	9	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	90	67	350	30	149	34	579	23	930	19	1162	17	0	.	0	.	0	.	14	100	0	.	0	.	0	.	0	.	0	.	15	77	42	87	75	52	0	.	-5	100	162	61	0	.	9	.	0	.	0	.	0	.	0	.	0	.	24	80	0	.	0	.	0	.	0	.	0	.	33	66	104	41	69	54	0	.	0	.	0	.	74	45	24	79	0	.	0	.	36	77	54	100	38	100	35	65	26	65	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	12	.	0	.	0	.	0	.	0	.	581	20	601	21	425	30	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	6698	7
	41-50 cm	0	.	0	.	0	.	0	.	0	.	0	.	652	23	25	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	131	47	514	27	130	53	562	21	807	19	1198	16	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	19	100	48	84	24	53	0	.	8	100	80	71	0	.	0	.	0	.	0	.	0	.	0	.	0	.	20	73	0	.	0	.	0	.	0	.	0	.	80	45	186	32	35	54	0	.	0	.	0	.	86	57	18	58	0	.	6	.	49	86	22	80	45	87	26	51	93	58	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	18	.	0	.	0	.	0	.	0	.	577	19	616	24	553	25	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	6630	6
	51-60 cm	0	.	0	.	0	.	0	.	0	.	0	.	357	25	9	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	36	60	379	30	103	41	428	27	452	23	605	23	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	22	100	17	73	36	75	0	.	19	73	43	81	0	.	-3	.	0	.	0	.	0	.	0	.	0	.	42	100	0	.	0	.	0	.	0	.	0	.	52	52	179	47	41	75	0	.	0	.	0	.	53	57	9	100	0	.	0	.	32	74	55	100	43	71	14	84	25	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	4	.	0	.	0	.	0	.	0	.	503	21	403	25	263	26	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	4219	8
	61-70 cm	0	.	0	.	0	.	0	.	0	.	0	.	309	31	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	40	73	141	36	49	82	148	32	287	29	135	35	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	16	100	29	71	16	100	0	.	15	100	21	71	0	.	0	.	0	.	0	.	0	.	0	.	0	.	47	75	0	.	0	.	0	.	0	.	0	.	45	58	50	61	10	100	0	.	0	.	0	.	23	73	21	100	0	.	15	.	12	100	0	.	0	.	0	.	77	60	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	339	35	27	71	123	46	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	1995	11
	71-80 cm	0	.	0	.	0	.	0	.	0	.	0	.	73	52	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	31	72	107	51	13	100	112	46	36	71	57	50	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	8	100	36	100	0	.	0	.	16	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	45	59	33	100	16	100	0	.	0	.	0	.	22	100	0	.	0	.	17	.	16	100	0	.	24	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	307	30	36	71	8	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	1013	15
	81-90 cm	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	36	71	23	100	15	100	62	60	0	.	60	59	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	25	71	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	14	100	28	72	18	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	16	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	66	58	20	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	382	22
	91-100 cm	0	.	0	.	0	.	0	.	0	.	0	.	18	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	56	71	0	.	22	100	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	.	14	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	32	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	155	40
	>100 cm	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	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	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	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	31	100	0	0	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	114	60
	total	0	.	0	.	0	.	0	.	0	.	0	.	3153	17	66	96	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	478	45	1899	22	652	29	2385	18	3220	16	4266	13	0	.	0	.	0	.	36	97	0	.	0	.	0	.	0	.	0	.	133	65	183	63	324	41	0	.	48	78	468	44	0	.	44	.	0	.	0	.	0	.	0	.	0	.	145	64	0	.	0	.	0	.	0	.	0	.	306	37	709	30	246	45	1	.	0	.	0	.	307	41	86	59	16	.	41	.	173	66	157	90	158	84	117	52	317	56	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	42	.	0	.	0	.	0	.	0	.	3040	16	2327	19	1922	21	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	27466	5
high-montane	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	12-20 cm	0	.	0	.	0	.	0	.	1	.	0	.	368	19	26	56	0	.	4	71	0	.	0	.	0	.	0	.	4	100	54	53	84	44	3	71	0	.	15	62	123	31	124	33	211	22	517	15	277	20	0	.	29	72	0	.	89	45	0	.	0	.	0	.	4	.	0	.	16	77	90	37	31	48	0	.	4	100	48	43	13	65	10	82	0	.	0	.	0	.	0	.	0	.	15	54	107	49	3	71	0	.	0	.	0	.	42	33	57	37	86	31	6	57	0	.	0	.	73	39	18	59	23	62	12	55	18	74	138	37	13	57	39	57	90	56	0	.	0	.	2	100	0	.	0	.	4	72	0	.	0	.	16	70	0	.	0	.	0	.	0	.	528	17	364	18	297	23	1	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	4098	5
	21-30 cm	0	.	0	.	0	.	0	.	0	.	0	.	916	18	85	42	0	.	4	100	0	.	0	.	0	.	0	.	31	71	118	63	201	49	17	79	0	.	53	64	404	29	326	28	496	23	1147	15	823	19	0	.	59	79	0	.	130	49	0	.	0	.	0	.	13	.	0	.	93	69	214	36	72	45	0	.	18	100	170	39	27	84	8	100	0	.	0	.	0	.	0	.	0	.	62	58	158	44	20	72	0	.	0	.	0	.	64	47	89	38	211	36	11	88	0	.	0	.	97	43	28	70	30	74	63	47	68	74	265	36	23	53	74	47	127	49	0	.	0	.	28	61	0	.	0	.	11	100	0	.	23	.	41	71	0	.	0	.	0	.	0	.	915	16	549	19	579	22	9	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	8970	5
	31-40 cm	0	.	0	.	0	.	0	.	0	.	0	.	1455	16	218	49	0	.	13	100	0	.	0	.	0	.	0	.	32	76	141	54	285	41	43	65	0	.	49	54	785	24	383	30	823	21	1773	14	1313	17	0	.	34	100	0	.	162	39	0	.	0	.	0	.	0	.	0	.	30	51	276	33	156	42	0	.	27	106	184	49	75	100	11	71	0	.	0	.	0	.	0	.	0	.	88	56	282	37	67	73	0	.	0	.	0	.	158	54	196	47	316	28	16	62	0	.	0	.	51	50	29	70	67	60	121	55	144	65	288	31	113	64	243	51	212	41	0	.	0	.	53	60	0	.	0	.	36	72	4	.	24	.	57	62	0	.	0	.	0	.	0	.	936	17	785	19	762	18	4	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	13319	5
	41-50 cm	0	.	0	.	0	.	0	.	0	.	0	.	1680	16	120	48	0	.	0	.	0	.	0	.	0	.	0	.	65	86	82	49	187	52	42	75	0	.	71	55	678	23	524	26	1149	19	1825	14	835	17	0	.	-3	100	0	.	148	47	0	.	0	.	0	.	0	.	0	.	82	65	197	36	133	42	0	.	36	100	246	46	50	74	111	74	0	.	0	.	0	.	0	.	0	.	81	54	153	42	48	62	0	.	0	.	0	.	138	42	112	34	250	25	15	75	0	.	0	.	44	45	46	100	33	71	76	57	78	59	167	36	176	55	147	34	232	35	0	.	0	.	83	58	0	.	0	.	33	71	16	.	33	.	46	62	0	.	0	.	0	.	0	.	938	19	524	21	765	20	40	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	12533	5
	51-60 cm	0	.	0	.	0	.	0	.	0	.	0	.	1280	17	60	54	0	.	-4	100	0	.	0	.	0	.	0	.	16	100	-1	100	36	54	85	87	0	.	60	86	687	23	455	36	843	23	1287	15	526	21	0	.	0	.	0	.	56	58	0	.	0	.	0	.	0	.	0	.	6	100	150	40	95	47	0	.	0	.	280	48	24	87	142	69	0	.	0	.	0	.	0	.	0	.	73	58	74	54	48	100	0	.	0	.	0	.	185	45	160	35	152	37	9	100	0	.	0	.	37	61	12	100	103	61	21	89	67	58	120	41	122	49	71	47	131	45	0	.	0	.	50	82	0	.	0	.	0	.	22	.	10	.	19	100	0	.	0	.	0	.	0	.	880	21	398	22	757	25	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	9603	6
	61-70 cm	0	.	0	.	0	.	0	.	0	.	0	.	374	33	38	100	0	.	17	100	0	.	0	.	0	.	0	.	0	.	0	.	40	74	0	.	0	.	147	72	333	39	237	33	509	27	819	22	210	39	0	.	0	.	0	.	44	72	0	.	0	.	0	.	0	.	0	.	9	100	117	40	57	62	0	.	15	100	171	53	22	100	11	100	0	.	0	.	0	.	0	.	0	.	0	.	18	100	0	.	0	.	0	.	0	.	51	74	143	60	75	55	20	71	0	.	0	.	0	.	30	73	0	.	18	100	81	100	54	77	60	50	58	50	13	100	0	.	0	.	11	100	0	.	0	.	0	.	0	.	0	.	13	100	0	.	0	.	0	.	0	.	211	35	138	40	294	29	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	4458	9
	71-80 cm	0	.	0	.	0	.	0	.	0	.	0	.	157	40	0	.	0	.	48	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	50	100	120	42	197	49	183	49	460	26	110	47	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	63	58	0	.	57	100	19	100	0	.	43	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	16	100	0	.	0	.	0	.	14	100	18	100	88	54	0	.	0	.	0	.	38	74	0	.	58	73	0	.	57	100	46	100	16	100	119	63	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	224	31	54	58	162	50	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	2417	12
	81-90 cm	0	.	0	.	0	.	0	.	0	.	0	.	34	75	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	66	59	0	.	0	.	57	72	79	59	66	72	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	11	100	0	.	0	.	0	.	0	.	74	77	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	43	100	0	.	0	.	0	.	18	100	27	100	16	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	54	71	53	58	51	72	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	649	21
	91-100 cm	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	21	100	0	.	49	100	0	.	95	76	16	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	38	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	31	100	28	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	31	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	20	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	330	34
	>100 cm	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	28	100	0	.	0	.	43	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	.	34	100	0	.	38	100	0	.	0	.	0	.	57	100	0	.	63	100	0	.	0	.	0	.	0	.	20	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	0	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	281	40
	total	0	.	0	.	0	.	0	.	1	.	0	.	6264	13	546	40	0	.	82	84	0	.	0	.	0	.	0	.	149	73	394	49	833	36	190	67	0	.	531	49	3158	20	2296	22	4269	17	8045	11	4176	15	0	.	119	82	0	.	629	35	0	.	0	.	0	.	17	.	0	.	246	56	1044	29	607	38	0	.	158	71	1229	33	210	71	336	65	0	.	0	.	0	.	0	.	0	.	319	48	794	32	202	62	0	.	0	.	0	.	718	31	804	28	1216	23	76	62	0	.	0	.	440	34	163	62	377	53	311	49	531	51	1135	28	541	44	770	33	805	34	0	.	0	.	228	54	0	.	0	.	83	71	42	.	91	.	192	49	0	.	0	.	0	.	0	.	4684	13	2885	15	3667	15	54	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	56658	4
lower and upper montane	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	12-20 cm	53	39	5	71	27	76	89	34	186	29	368	22	662	14	918	12	300	23	1032	13	0	0	35	56	98	32	0	.	59	58	177	27	437	22	226	30	0	.	409	23	130	26	156	25	18	55	136	32	0	.	787	15	166	26	221	26	468	18	51	38	216	28	67	41	98	35	188	21	200	29	101	35	286	27	213	32	117	26	305	25	130	40	346	18	173	34	73	37	189	26	78	59	138	32	228	24	192	29	190	28	107	37	0	.	16	68	0	.	81	35	0	.	152	30	137	31	83	38	244	25	197	33	154	32	94	31	56	50	11	57	119	37	36	50	204	28	117	36	7	100	148	26	29	59	64	38	188	21	69	27	156	27	55	37	44	40	61	59	14	60	32	54	0	.	11	95	324	21	106	33	112	50	13	89	189	30	132	32	0	.	26	100	4	100	0	.	14334	3
	21-30 cm	191	35	25	100	52	63	211	39	656	26	1080	22	1239	12	1926	11	737	20	1956	12	12	100	116	46	226	28	0	.	82	59	322	31	899	19	498	26	0	.	826	23	213	29	403	26	1	433	142	38	0	.	1783	13	460	27	345	25	911	17	101	38	377	24	259	35	123	31	523	23	360	30	164	40	502	27	618	24	414	36	585	20	328	28	1030	17	275	36	195	49	468	25	47	56	472	24	357	24	539	28	271	28	221	27	0	.	63	61	0	.	60	39	0	.	172	31	239	26	141	36	184	27	235	34	180	32	203	35	45	46	92	45	142	37	71	45	408	25	258	40	34	100	382	25	40	72	218	32	374	22	212	29	310	28	135	36	90	61	85	48	86	40	160	51	0	.	0	.	538	20	201	35	257	43	64	47	549	25	395	26	0	.	36	100	14	100	0	.	30218	3
	31-40 cm	328	33	0	.	40	82	334	33	783	24	1293	19	2426	13	3457	12	1305	19	2481	13	45	84	191	48	309	30	0	.	96	63	519	31	1195	19	894	29	0	.	990	20	295	31	462	25	48	51	96	41	0	.	2392	12	703	28	1159	22	1446	18	199	38	537	21	332	44	163	32	778	21	503	28	311	38	652	25	795	25	507	29	1002	21	574	29	1248	18	257	39	393	33	548	26	118	48	574	24	547	26	744	24	457	29	339	32	0	.	61	58	0	.	77	45	0	.	113	35	217	31	77	42	142	27	177	36	213	48	185	34	41	55	103	53	123	43	128	41	442	29	335	34	140	86	455	23	34	73	201	35	639	23	283	27	494	25	258	29	107	54	317	56	131	43	269	56	0	.	6	100	430	22	523	29	247	50	210	43	974	21	621	25	0	.	101	78	17	100	0	.	43753	3
	41-50 cm	155	36	0	.	0	.	264	33	588	27	1289	21	2486	13	4255	11	1417	18	1755	12	26	100	104	61	476	27	0	.	171	56	405	29	1128	20	504	27	0	.	907	19	320	32	489	24	50	63	76	49	0	.	1992	13	671	26	1020	21	1430	19	268	32	677	22	268	36	194	31	919	20	336	34	283	40	654	28	673	29	335	29	983	23	649	25	1430	16	123	52	358	27	393	29	273	46	456	25	585	23	820	25	464	28	421	32	0	.	65	62	0	.	117	40	0	.	44	50	154	44	58	54	218	28	131	42	101	35	176	42	50	62	82	50	97	38	131	52	398	29	464	32	31	71	324	27	81	64	284	34	468	21	281	30	421	27	344	32	123	62	145	44	130	43	227	46	0	.	0	.	384	24	528	31	294	35	250	41	881	24	481	31	0	.	42	74	45	100	0	.	41586	3
	51-60 cm	88	53	0	.	0	.	162	52	203	38	843	24	2091	15	2697	12	1083	19	934	17	49	100	77	61	154	37	0	.	43	75	270	35	703	24	247	39	0	.	431	28	270	35	397	26	9	100	137	49	0	.	1031	15	788	27	642	24	687	25	102	41	317	32	143	49	245	36	753	23	190	32	228	42	490	30	480	29	204	44	533	29	236	42	1056	21	77	46	215	44	110	40	39	59	121	52	353	30	483	27	472	36	126	55	0	.	146	65	0	.	129	48	0	.	42	59	56	56	50	100	142	38	53	58	82	49	169	54	16	90	40	74	215	43	215	50	214	36	302	37	52	100	272	44	38	100	259	40	287	27	224	33	253	37	194	39	40	71	90	65	47	59	140	44	36	.	0	.	278	42	408	35	168	43	150	64	466	26	177	39	0	.	17	100	0	.	0	.	26479	3
	61-70 cm	0	.	39	100	0	.	43	71	62	78	35	71	727	20	1170	15	387	30	312	26	44	100	17	100	76	51	0	.	70	100	98	52	438	29	147	51	0	.	214	38	87	60	172	46	17	100	57	53	0	.	461	25	178	49	121	48	198	35	98	41	108	48	0	.	107	51	177	34	56	59	222	51	112	61	156	44	155	47	128	46	178	43	443	28	25	100	99	83	56	58	14	100	0	.	242	41	166	46	274	36	49	73	0	.	35	71	0	.	45	74	0	.	11	82	18	73	17	100	80	42	45	73	52	47	36	72	73	100	26	100	55	58	18	100	111	63	184	47	0	.	90	43	0	.	152	44	30	71	205	41	133	45	45	56	0	.	123	61	31	71	0	.	0	.	0	.	62	51	78	62	145	46	45	100	68	51	50	58	0	.	27	100	0	.	0	.	10122	5
	71-80 cm	0	.	0	.	0	.	0	.	48	72	25	100	216	41	740	23	136	45	99	50	0	.	0	.	28	100	0	.	0	.	35	80	90	62	23	100	0	.	130	43	0	.	41	71	35	100	63	82	0	.	67	59	0	.	0	.	85	58	86	60	123	67	31	100	122	55	121	68	0	.	26	100	34	100	0	.	44	100	27	75	91	52	281	49	27	100	0	.	0	.	0	.	24	100	123	54	68	59	212	54	0	.	0	.	0	.	0	.	89	91	0	.	0	.	20	100	0	.	12	100	63	72	0	.	0	.	0	.	0	.	29	100	23	100	0	.	52	100	0	.	54	100	0	.	17	100	64	59	24	100	42	71	69	75	0	.	0	.	55	100	0	.	0	.	0	.	28	75	24	100	53	71	0	.	87	61	28	100	0	.	0	.	0	.	0	.	4135	10
	81-90 cm	0	.	0	.	0	.	55	71	0	.	0	.	67	60	327	34	31	100	59	71	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	50	72	8	100	24	100	0	.	30	100	17	100	32	100	0	.	0	.	0	.	0	.	0	.	26	100	0	.	30	100	0	.	34	100	0	.	0	.	36	100	66	71	0	.	0	.	28	100	0	.	0	.	39	100	0	.	28	100	0	.	0	.	0	.	0	.	33	100	0	.	0	.	0	.	0	.	22	71	0	.	0	.	0	.	0	.	19	100	28	100	21	100	0	.	0	.	0	.	19	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	19	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	1148	16
	91-100 cm	0	.	0	.	0	.	0	.	0	.	0	.	85	71	49	100	0	.	29	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	22	100	0	.	48	100	0	.	0	.	0	.	0	.	0	.	25	100	0	.	0	.	0	.	0	.	0	.	40	100	0	.	31	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	21	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	22	100	0	.	0	.	0	.	0	.	0	.	0	.	19	100	0	.	0	.	0	.	80	71	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	.	493	27
	>100 cm	0	.	0	.	0	.	0	.	0	.	0	.	70	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	.	37	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	20	100	0	.	0	.	0	.	0	.	0	.	0	.	48	100	0	.	0	.	31	100	0	.	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	.	0	.	0	.	0	.	0	.	0	.	0	.	229	45
	total	815	32	68	72	118	61	1157	28	2527	23	4933	17	10069	10	15539	9	5396	15	8657	10	175	77	541	43	1367	25	0	.	521	49	1827	25	4890	16	2562	22	0	.	3956	17	1314	25	2170	19	186	52	730	29	0	.	8568	10	2982	22	3540	19	5224	15	905	30	2355	18	1141	31	1053	27	3553	17	1645	25	1364	30	2730	22	2969	21	1778	26	3562	18	2221	21	5899	15	956	29	1332	28	1793	21	568	37	1784	20	2474	19	3011	20	2409	22	1262	27	0	.	387	55	0	.	631	34	0	.	582	24	864	25	427	37	1074	20	902	26	806	28	862	33	281	53	392	48	807	30	644	39	1778	23	1791	27	265	74	1744	21	223	58	1195	29	2051	17	1299	24	1809	21	1100	26	403	45	821	41	495	39	828	41	36	.	17	97	2063	18	1868	25	1298	29	731	40	3214	19	1885	23	0	.	248	72	80	100	0	.	172498	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	314	19	331	19	333	26	274	25	0	.	0	.	84	45	147	28	1067	14	14	72	52	33	153	32	101	38	13	.	86	44	93	42	19	.	137	36	0	.	0	.	28	63	17	51	0	.	0	.	0	.	260	22	136	49	183	30	44	52	35	48	0	.	49	45	12	.	0	.	3	100	55	73	33	59	50	36	116	48	31	52	114	44	10	.	304	21	69	34	64	39	155	32	145	32	25	59	0	.	10	90	124	33	208	28	218	27	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	44	81	0	.	32	62	56	47	45	59	6	.	64	41	32	67	8	72	125	35	60	51	0	.	64	57	88	41	178	36	72	45	70	60	0	.	114	52	0	.	0	.	111	37	59	61	23	51	113	31	27	50	123	32	132	31	125	29	164	28	0	.	7651	4
	21-30 cm	785	19	540	20	509	27	555	21	0	.	0	.	169	46	408	31	1972	12	48	62	165	37	305	30	301	31	4	.	240	38	308	32	24	.	336	29	0	.	20	.	58	67	74	56	0	.	0	.	0	.	821	21	362	31	453	25	70	64	72	36	0	.	108	52	30	.	0	.	56	81	9	100	51	58	222	38	216	49	87	55	121	49	-1	.	597	25	284	28	180	37	228	30	377	29	43	86	0	.	63	62	291	36	441	28	382	25	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	58	58	0	.	61	61	95	44	40	69	0	.	141	37	65	55	40	66	236	42	163	52	0	.	90	44	219	36	316	32	124	38	72	48	0	.	359	34	0	.	0	.	98	40	64	55	125	51	366	27	96	52	252	36	246	28	322	31	327	28	0	.	16355	4
	31-40 cm	950	17	987	19	559	23	1110	20	0	.	0	.	327	37	391	29	3142	11	23	75	263	31	309	32	396	29	0	.	522	30	381	32	52	.	496	29	0	.	15	.	96	65	88	51	0	.	0	.	0	.	987	19	524	23	774	25	115	59	157	50	0	.	155	56	15	.	0	.	78	76	29	100	81	65	345	34	172	65	68	61	182	47	0	.	807	24	461	28	309	44	381	30	370	29	77	71	0	.	81	71	423	35	536	32	631	25	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	3	137	0	.	41	61	70	51	46	60	30	.	227	43	156	55	41	71	381	31	103	43	0	.	87	54	227	39	354	34	180	46	65	49	0	.	372	36	0	.	0	.	29	57	94	61	309	46	689	26	180	54	511	26	589	26	603	28	654	28	0	.	23909	4
	41-50 cm	983	21	864	21	438	24	1287	20	0	.	0	.	325	42	442	32	3774	11	43	82	317	33	300	35	245	36	23	.	383	33	361	36	59	.	460	29	0	.	36	.	75	65	88	56	0	.	0	.	0	.	808	21	523	27	642	24	99	58	122	54	0	.	72	57	0	.	0	.	9	100	12	100	68	70	335	35	133	52	73	72	131	53	0	.	500	22	750	26	82	45	433	34	260	36	18	100	0	.	81	63	407	34	677	30	372	25	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	1	100	0	.	3	100	45	46	22	71	15	.	215	42	91	69	79	75	223	35	74	68	0	.	87	51	132	44	161	40	45	54	69	58	0	.	207	36	0	.	0	.	63	48	87	57	326	36	806	24	166	45	637	29	468	28	539	25	647	28	0	.	22317	4
	51-60 cm	559	25	734	25	369	29	857	23	0	.	0	.	203	42	301	38	2432	13	0	.	278	33	120	42	134	42	13	.	255	38	117	54	21	.	267	43	0	.	15	.	56	75	67	62	0	.	0	.	0	.	518	29	316	35	324	36	77	61	55	70	0	.	18	148	0	.	0	.	15	100	15	100	14	100	166	46	31	100	26	100	108	44	0	.	337	29	423	34	0	.	217	38	56	68	0	.	0	.	39	100	295	43	286	34	336	29	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	20	100	0	.	17	100	37	70	14	100	0	.	61	48	17	100	22	100	154	33	22	71	0	.	35	100	42	52	74	48	19	74	27	59	0	.	115	48	0	.	0	.	94	50	48	71	172	56	249	35	37	64	455	30	244	32	347	36	277	30	0	.	13066	5
	61-70 cm	327	31	211	38	65	60	116	46	0	.	0	.	85	61	172	53	928	18	0	.	155	44	41	100	14	100	20	.	58	58	75	50	15	.	170	65	0	.	39	.	17	100	0	.	0	.	0	.	0	.	173	50	30	71	97	64	18	100	0	.	0	.	16	100	0	.	0	.	0	.	0	.	0	.	0	.	90	70	11	100	80	100	0	.	99	41	249	44	16	100	34	71	46	72	0	.	0	.	19	100	69	50	80	61	233	37	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	17	100	0	.	0	.	0	.	98	60	20	100	0	.	146	53	27	71	0	.	0	.	0	.	17	100	0	.	46	76	0	.	18	100	0	.	0	.	21	80	0	.	23	100	129	47	23	100	157	44	95	54	145	44	167	38	0	.	5017	8
	71-80 cm	65	58	64	73	56	71	251	45	0	.	0	.	0	.	206	52	447	25	0	.	61	71	0	.	0	.	0	.	30	100	46	71	0	.	51	71	0	.	0	.	0	.	27	100	0	.	0	.	0	.	50	100	44	71	23	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	113	71	0	.	24	100	0	.	0	.	0	.	0	.	20	100	22	100	85	51	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	11	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	43	71	0	.	0	.	21	100	0	.	0	.	0	.	21	100	0	.	23	100	0	.	0	.	0	.	0	.	0	.	49	100	0	.	58	71	45	71	25	100	21	100	0	.	2000	13
	81-90 cm	24	100	55	71	38	100	0	.	0	.	0	.	0	.	88	59	275	43	0	.	46	100	33	100	0	.	0	.	0	.	26	100	0	.	69	71	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	22	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	38	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	23	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	29	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	39	100	0	.	0	.	23	100	0	.	28	100	0	.	856	21
	91-100 cm	0	.	31	100	0	.	0	.	0	.	0	.	0	.	0	.	39	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	20	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	40	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	.	37	100	0	.	0	.	0	.	0	.	168	46
	>100 cm	0	.	36	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	54	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	.	89	72
	total	4008	15	3852	16	2367	18	4450	16	0	.	0	.	1192	35	2156	24	14076	9	128	62	1337	26	1314	24	1191	26	73	.	1573	29	1406	29	190	.	2006	25	0	.	125	.	330	54	361	48	0	.	0	.	0	.	3616	16	1958	22	2496	21	424	52	440	42	0	.	417	47	56	.	0	.	160	71	120	77	248	60	1117	31	758	47	296	52	737	38	8	.	2681	18	2349	24	651	36	1472	25	1255	26	163	67	0	.	294	60	1630	28	2273	23	2298	20	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	138	60	0	.	171	58	302	42	166	59	51	.	806	37	381	49	190	63	1338	28	448	41	0	.	384	41	708	34	1099	27	439	38	371	42	0	.	1206	29	0	.	0	.	415	32	352	46	979	36	2440	21	528	44	2230	23	1842	23	2106	23	2284	22	0	.	91427	3
hyperinsubric and colline	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	12-20 cm	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	138	44	0	.	4	.	0	.	3	100	186	30	1	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	.	3	.	10	100	37	33	40	51	137	38	264	25	656	16	102	34	200	35	255	23	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	30	.	0	.	0	.	28	75	0	.	0	.	25	.	0	.	0	.	0	.	130	32	71	42	22	41	0	.	0	.	0	.	0	.	0	.	35	66	0	.	0	.	0	.	2375	8
	21-30 cm	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	84	39	0	.	8	.	0	.	-5	100	123	37	2	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	.	6	101	36	62	61	58	127	35	213	28	546	19	107	39	87	30	277	27	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	21	.	0	.	0	.	10	74	0	.	0	.	6	.	0	.	0	.	0	.	120	37	69	42	24	66	0	.	0	.	0	.	0	.	0	.	35	71	0	.	0	.	0	.	1957	8
	31-40 cm	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	65	54	0	.	0	.	0	.	0	.	49	48	14	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	7	.	0	.	16	58	37	60	56	60	143	31	232	29	73	39	81	37	181	28	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	17	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	104	32	44	43	39	70	0	.	0	.	0	.	0	.	0	.	81	87	0	.	0	.	0	.	1239	11
	41-50 cm	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	54	84	0	.	0	.	0	.	15	100	84	52	24	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	.	32	.	0	.	26	62	13	58	31	64	82	51	163	33	79	39	53	53	134	47	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	-4	.	0	.	0	.	3	100	0	.	0	.	0	.	0	.	0	.	0	.	80	53	9	100	31	62	0	.	0	.	0	.	0	.	0	.	34	60	0	.	0	.	0	.	946	14
	51-60 cm	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	28	95	0	.	0	.	0	.	37	76	47	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	.	24	50	13	72	20	75	56	46	41	45	42	62	40	50	42	51	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	7	143	13	100	24	100	0	.	0	.	0	.	0	.	0	.	12	100	0	.	0	.	0	.	446	18
	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	.	5	100	14	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	12	100	8	100	0	.	0	.	0	.	19	70	34	60	10	100	19	59	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	7	100	0	.	11	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	137	27
	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	.	89	67	0	.	0	.	18	100	68	53	20	100	0	.	37	63	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	11	100	0	.	0	.	0	.	0	.	0	.	28	100	0	.	0	.	0	.	270	31
	81-90 cm	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	24	74	0	.	0	.	0	.	46	77	0	.	0	.	3	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	29	100	0	.	0	.	0	.	102	48
	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	.	28	71	0	.	0	.	0	.	53	75	0	.	0	.	27	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	.	0	.	0	.	0	.	0	.	108	45
	>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	.	44	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	.	23	100	0	.	0	.	0	.	37	100	323	57	0	.	72	66	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	500	39
	total	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	369	39	0	.	11	.	0	.	50	77	537	30	55	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	.	42	.	27	100	310	41	164	51	372	31	776	26	1860	15	781	32	471	27	1049	23	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	64	.	0	.	0	.	40	73	0	.	0	.	31	.	0	.	0	.	0	.	447	29	207	35	161	45	0	.	0	.	0	.	0	.	0	.	253	63	0	.	0	.	0	.	8079	7
total	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	12-20 cm	367	17	336	19	360	25	363	21	187	29	368	22	1284	9	1091	11	1367	12	1051	12	52	33	188	28	198	25	13	.	148	34	324	21	540	19	366	23	138	44	438	22	363	16	346	18	350	15	1047	11	862	11	1047	12	331	25	404	20	614	16	86	30	216	28	116	30	113	32	188	21	255	25	265	24	392	21	263	27	245	26	417	19	257	28	374	17	477	18	141	25	254	22	232	29	283	22	271	21	299	25	204	27	231	25	208	28	237	25	54	31	210	18	146	24	297	23	402	20	739	15	440	17	416	23	437	18	150	31	81	39	192	29	198	26	124	31	315	25	181	28	40	58	158	24	184	30	124	31	192	21	161	29	244	23	252	27	141	32	131	42	14	60	146	42	915	12	658	13	873	12	167	30	135	42	126	29	216	27	256	23	167	28	151	30	167	27	0	.	30562	2
	21-30 cm	976	16	565	20	560	25	766	18	656	26	1080	22	2917	9	2441	10	2709	10	2008	12	177	35	421	25	528	21	4	.	353	30	748	21	1123	18	851	19	84	39	948	21	1028	16	963	16	815	18	1963	11	1882	11	2604	11	881	20	798	18	1120	15	172	27	377	24	367	29	167	30	523	23	533	25	406	25	724	21	840	20	652	28	916	16	476	24	1068	17	872	21	479	26	648	21	275	27	849	19	471	21	697	23	355	24	511	24	441	28	445	23	91	36	299	22	330	26	310	23	452	19	687	17	428	18	363	24	498	20	327	26	134	42	457	25	260	26	223	27	569	21	398	29	99	50	451	23	297	35	382	29	385	22	312	23	553	21	495	23	219	33	157	34	86	40	519	28	1676	12	1166	13	1716	12	273	29	382	33	431	24	645	23	647	21	281	26	358	30	342	27	0	.	62933	2
	31-40 cm	1278	15	987	19	598	23	1444	17	783	24	1293	19	5188	8	4075	10	4447	9	2517	13	308	29	501	27	705	21	0	.	650	26	1041	21	1532	17	1434	21	65	54	1144	18	1547	16	1094	16	1449	15	2957	11	3089	10	3378	10	1260	18	1934	16	1737	16	356	31	537	21	487	35	178	30	778	21	626	24	657	23	968	19	1140	20	700	26	1416	18	830	24	1268	18	1064	20	854	22	857	23	499	26	944	18	736	22	1026	20	605	25	763	24	536	32	699	23	192	46	405	27	437	23	185	28	360	22	309	24	355	18	312	24	461	26	310	30	221	45	495	25	344	30	452	31	711	22	562	27	296	50	549	20	432	28	303	28	676	22	374	24	745	20	681	21	287	35	382	47	131	43	640	31	1935	11	1492	13	1686	12	620	26	556	34	899	22	1154	20	1132	18	670	26	704	26	670	27	0	.	90085	2
	41-50 cm	1138	19	864	21	438	24	1550	17	588	27	1289	21	5143	9	4841	10	5191	9	1798	12	343	32	404	30	721	21	23	.	619	27	848	21	1374	18	1006	19	54	84	1145	17	1610	15	1230	16	1776	14	2900	10	2530	10	2800	11	1191	18	1662	16	1677	17	391	28	677	22	340	31	194	31	919	20	447	29	540	26	880	22	1008	22	512	24	1381	19	830	22	1540	16	623	21	1108	20	475	25	706	27	716	20	705	20	974	22	593	24	828	23	677	30	470	23	218	31	479	18	305	22	90	35	236	34	221	28	438	19	249	31	268	28	259	33	177	39	279	27	363	31	325	27	739	20	678	25	122	54	486	24	301	31	357	30	501	20	387	25	585	22	570	23	168	47	215	35	130	43	434	30	1829	12	1183	15	1808	13	655	27	620	25	1056	20	1047	21	1118	21	502	27	581	24	692	27	0	.	84955	2
	51-60 cm	647	22	734	25	369	29	1019	21	203	38	843	24	3930	10	3067	11	3515	10	930	17	327	32	197	35	288	28	13	.	314	33	386	29	760	22	599	28	28	95	541	25	1414	15	1039	20	1317	17	1992	11	1505	14	1549	14	1104	22	966	20	821	22	157	36	317	32	160	47	245	36	753	23	232	28	410	28	635	25	646	24	255	38	882	24	368	30	1195	20	413	25	638	27	110	40	256	34	178	41	468	26	557	24	559	32	421	35	286	34	482	28	237	37	510	23	206	32	72	43	112	36	91	59	281	25	115	35	227	34	210	45	115	42	231	35	416	28	313	36	370	27	363	32	69	79	344	37	192	33	281	38	287	27	281	30	305	32	291	29	58	54	117	52	47	59	255	33	1539	14	891	16	1414	17	456	32	340	35	400	32	503	25	633	24	256	31	364	35	277	30	0	.	54512	2
	61-70 cm	327	31	250	35	65	60	159	38	62	78	35	71	1495	15	1380	15	1315	16	329	25	199	40	58	77	90	46	20	.	129	61	173	36	493	26	318	42	0	.	441	32	591	25	458	26	673	22	1237	17	517	21	634	23	208	43	218	39	260	30	98	41	108	48	16	100	107	51	177	34	80	47	368	34	185	42	156	44	275	36	331	33	280	40	454	28	124	38	348	39	72	50	48	58	46	72	289	37	184	42	293	34	117	42	80	61	268	34	108	44	246	40	85	50	31	54	18	73	36	60	150	30	105	43	71	38	69	50	166	66	96	53	115	38	76	45	201	42	282	37	20	100	100	40	146	53	179	39	30	71	205	41	133	45	75	44	0	.	169	49	31	71	18	100	686	21	165	35	511	21	78	62	168	42	174	44	91	46	207	36	95	54	172	40	167	38	0	.	22110	4
	71-80 cm	65	58	64	73	56	71	251	45	48	72	25	100	446	26	946	21	583	22	147	47	61	71	0	.	28	100	0	.	30	100	81	53	90	62	74	58	0	.	211	37	227	33	278	38	330	33	598	23	266	26	117	54	44	71	23	100	85	58	86	60	123	67	31	100	122	55	121	68	0	.	34	80	133	46	0	.	101	71	62	52	91	52	324	45	27	100	113	71	0	.	24	100	24	100	123	54	68	59	228	50	20	100	22	100	85	51	59	51	241	45	104	48	0	.	38	71	68	53	110	42	63	72	96	51	28	72	74	81	46	100	68	59	142	55	0	.	52	100	0	.	54	100	43	71	17	100	64	59	45	71	42	71	69	75	0	.	21	100	55	100	23	100	589	20	100	42	209	41	24	100	53	71	49	100	87	61	86	58	73	58	25	100	21	100	0	.	10071	6
	81-90 cm	24	100	55	71	38	100	55	71	0	.	0	.	101	47	415	30	306	40	59	71	46	100	33	100	0	.	0	.	0	.	26	100	0	.	69	71	0	.	101	45	23	100	65	60	126	44	120	46	183	37	30	100	39	71	32	100	0	.	0	.	0	.	0	.	0	.	26	100	11	100	30	100	0	.	34	100	0	.	98	60	36	100	66	71	38	100	0	.	28	100	0	.	0	.	39	100	0	.	28	100	0	.	23	100	0	.	14	100	86	50	18	100	0	.	0	.	46	77	65	71	0	.	3	100	0	.	18	100	45	72	45	73	21	100	16	100	0	.	0	.	19	100	29	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	149	39	95	45	71	59	0	.	0	.	39	100	0	.	0	.	52	71	0	.	28	100	0	.	3261	10
	91-100 cm	0	.	31	100	0	.	0	.	0	.	0	.	103	61	49	100	39	100	29	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	42	71	0	.	69	76	0	.	49	100	56	71	95	76	38	72	25	100	0	.	0	.	0	.	0	.	0	.	40	100	0	.	31	100	0	.	0	.	0	.	0	.	0	.	52	78	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	21	100	0	.	0	.	40	100	45	75	56	62	0	.	0	.	22	100	53	75	0	.	0	.	27	78	0	.	0	.	50	72	0	.	0	.	0	.	80	71	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	73	59	20	100	0	.	0	.	21	100	0	.	0	.	37	100	0	.	0	.	0	.	0	.	1296	16
	>100 cm	0	.	36	100	0	.	0	.	0	.	0	.	70	100	0	.	0	.	0	.	0	.	54	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	52	100	28	100	0	.	0	.	104	55	45	72	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	.	20	100	0	.	0	.	0	.	34	100	23	100	38	100	48	100	0	.	37	100	411	47	0	.	159	52	0	.	0	.	0	.	0	.	20	100	32	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	47	74	0	0	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	1292	21
	total	4822	13	3921	16	2486	18	5607	14	2528	23	4933	17	20678	7	18306	8	19472	7	8868	10	1512	25	1855	21	2558	18	73	.	2243	24	3627	18	5912	14	4759	16	369	39	5089	15	6830	12	5523	13	6892	12	13012	8	10916	8	12184	8	5058	15	6036	14	6314	13	1346	24	2355	18	1558	26	1127	26	3553	17	2184	21	2711	20	3917	17	4086	17	2742	22	5555	14	3168	18	6287	15	3638	15	3681	18	2443	18	2040	21	3039	16	3102	17	3805	17	2905	20	2891	19	2273	23	2727	18	1052	24	2553	15	1668	19	1032	18	1640	18	2287	14	2676	14	1623	17	2248	17	1352	25	985	33	1892	22	1808	21	1697	22	2953	18	2597	22	645	42	2161	19	1625	25	1643	24	2134	16	1765	20	2609	18	2434	18	874	28	1192	31	495	39	2035	24	9441	9	5770	11	8287	10	2274	22	2276	23	3172	19	3743	17	4115	16	2095	22	2354	22	2363	22	0	.	361078	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. 2281761. Birmensdorf, Swiss Federal Research Institute WSL

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