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 NFI1-NFI5
grid: 1.4 km grid, subgrids 1-5
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	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	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	.	3	.	3	71	228	24	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	10	89	5	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	.	108	47	22	53	3	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	382	20
	21-30 cm	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	16	.	0	.	0	.	20	62	346	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	.	3	100	26	85	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	185	36	112	70	39	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	747	19
	31-40 cm	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	13	.	0	.	0	.	74	58	703	26	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	18	100	24	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	.	314	31	8	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	1155	18
	41-50 cm	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	8	.	0	.	0	.	70	42	390	30	0	.	0	.	0	.	0	.	0	.	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	72	11	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	189	35	38	60	9	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	736	19
	51-60 cm	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	40	.	0	.	0	.	71	71	393	36	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	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	48	43	72	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	628	26
	61-70 cm	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	25	.	0	.	0	.	93	78	145	43	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	112	59	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	376	31
	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	.	38	100	92	52	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	59	61	19	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	208	35
	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	.	31	100	68	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	.	24	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	122	51
	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	.	34	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	34	100
	>100 cm	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	32	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	.	30	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	112	59
	total	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	101	.	0	.	3	.	432	50	2415	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	.	53	83	66	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	.	1136	26	242	47	51	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	4500	14
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	.	198	22	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	86	37	30	54	89	33	149	32	336	25	0	.	0	.	0	.	2	.	0	.	0	.	0	.	0	.	0	.	52	87	32	93	57	79	0	.	0	.	39	61	0	.	16	.	0	.	0	.	0	.	0	.	0	.	2	100	0	.	0	.	0	.	0	.	0	.	0	0	40	45	17	49	2	.	0	.	0	.	25	59	0	.	0	.	0	.	10	80	15	77	5	.	5	100	1	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	7	.	0	.	0	.	0	.	0	.	102	32	225	32	87	35	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	1630	10
	21-30 cm	0	.	0	.	0	.	0	.	0	.	0	.	770	24	39	89	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	285	31	103	67	283	47	283	33	735	25	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	46	100	35	64	120	65	0	.	0	.	82	68	0	.	64	.	0	.	0	.	0	.	0	.	0	.	13	100	0	.	0	.	0	.	0	.	0	.	13	72	177	48	43	55	0	.	0	.	0	.	42	57	6	100	0	.	5	.	25	100	32	82	0	.	37	101	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	8	.	0	.	0	.	0	.	0	.	305	33	371	31	323	44	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	4246	10
	31-40 cm	0	.	0	.	0	.	0	.	0	.	0	.	1117	27	15	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	42	72	399	30	86	55	565	34	621	32	1291	23	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	30	79	74	88	60	83	0	.	0	.	98	70	0	.	18	.	0	.	0	.	0	.	0	.	0	.	45	80	0	.	0	.	0	.	0	.	0	.	28	82	176	45	96	65	0	.	0	.	0	.	70	52	10	72	0	.	0	.	48	100	91	100	0	.	28	73	6	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	23	.	0	.	0	.	0	.	0	.	557	27	549	28	401	50	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	6546	9
	41-50 cm	0	.	0	.	0	.	0	.	0	.	0	.	872	28	42	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	105	66	527	30	79	64	593	28	485	30	1103	22	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	33	100	85	85	24	82	0	.	15	.	112	89	0	.	0	.	0	.	0	.	0	.	0	.	0	.	24	100	0	.	0	.	0	.	0	.	0	.	109	57	253	38	54	61	0	.	0	.	0	.	86	80	23	72	0	.	10	.	91	86	37	79	11	.	22	72	41	72	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	34	.	0	.	0	.	0	.	0	.	621	24	617	35	512	35	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	6620	9
	51-60 cm	0	.	0	.	0	.	0	.	0	.	0	.	302	33	16	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	48	71	409	40	96	65	372	39	238	36	735	30	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	37	100	12	100	24	100	0	.	21	.	62	100	0	.	-7	.	0	.	0	.	0	.	0	.	0	.	77	100	0	.	0	.	0	.	0	.	0	.	58	77	245	58	21	76	0	.	0	.	0	.	85	65	17	100	0	.	-1	.	59	74	92	100	36	.	4	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	8	.	0	.	0	.	0	.	0	.	587	27	397	36	296	37	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	4347	11
	61-70 cm	0	.	0	.	0	.	0	.	0	.	0	.	197	41	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	28	100	181	41	0	.	156	42	236	46	152	48	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	28	100	30	100	26	100	0	.	27	.	37	71	0	.	0	.	0	.	0	.	0	.	0	.	0	.	58	100	0	.	0	.	0	.	0	.	0	.	21	100	46	100	0	.	0	.	0	.	0	.	42	73	38	100	0	.	26	.	22	100	0	.	0	.	0	.	35	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	391	46	0	.	202	50	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	1977	15
	71-80 cm	0	.	0	.	0	.	0	.	0	.	0	.	50	71	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	31	100	162	58	23	100	62	58	63	71	76	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	.	34	100	0	.	0	.	0	.	0	.	0	.	40	100	0	.	0	.	29	.	30	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	382	37	64	71	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	1046	20
	81-90 cm	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	30	100	42	100	0	.	62	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	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	20	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	33	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	47	100	37	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	292	34
	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	.	99	72	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	24	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	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	.	180	52
	>100 cm	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	65	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	.	65	100
	total	0	.	0	.	0	.	0	.	0	.	0	.	3506	23	112	96	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	285	62	2090	25	418	47	2281	26	2076	25	4428	19	0	.	0	.	0	.	2	.	0	.	0	.	0	.	0	.	0	.	225	71	268	74	312	59	0	.	63	.	475	58	0	.	90	.	0	.	0	.	0	.	0	.	0	.	219	74	0	.	0	.	0	.	0	.	0	.	262	59	957	35	232	55	2	.	0	.	0	.	391	51	94	72	0	.	70	.	285	73	267	89	52	.	97	68	181	70	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	80	.	0	.	0	.	0	.	0	.	3049	21	2259	25	1821	32	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	26948	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	.	269	21	24	60	0	.	8	71	0	.	0	.	0	.	0	.	7	.	75	62	82	71	5	71	0	.	24	71	88	35	156	44	248	30	513	20	339	26	0	.	20	.	0	.	94	59	0	.	0	.	0	.	7	.	0	.	1	.	107	44	19	64	0	.	7	100	10	61	13	.	14	100	0	.	0	.	0	.	0	.	0	.	15	60	112	85	3	100	0	.	0	.	0	.	36	42	52	49	58	46	7	70	0	.	0	.	33	62	34	60	34	74	17	64	31	76	164	49	14	79	11	61	94	88	0	.	0	.	0	0	0	.	0	.	0	.	0	.	0	.	20	95	0	.	0	.	0	.	0	.	523	26	405	24	317	33	3	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	4114	8
	21-30 cm	0	.	0	.	0	.	0	.	0	.	0	.	683	22	98	59	0	.	7	100	0	.	0	.	0	.	0	.	30	.	156	77	127	81	22	100	0	.	70	83	462	38	274	40	582	30	1268	20	1014	25	0	.	26	.	0	.	160	64	0	.	0	.	0	.	24	.	0	.	29	.	185	51	83	56	0	.	31	100	67	52	38	.	14	100	0	.	0	.	0	.	0	.	0	.	53	60	150	77	25	100	0	.	0	.	0	.	44	62	52	79	208	54	23	76	0	.	0	.	73	63	52	71	47	86	85	54	111	83	330	45	34	62	86	62	85	69	0	.	0	.	26	72	0	.	0	.	0	.	0	.	0	.	41	100	0	.	0	.	0	.	0	.	744	23	609	24	613	28	18	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	8959	7
	31-40 cm	0	.	0	.	0	.	0	.	0	.	0	.	1559	21	240	60	0	.	23	100	0	.	0	.	0	.	0	.	16	.	188	65	140	65	57	79	0	.	78	61	840	30	296	36	853	28	1802	20	1417	21	0	.	0	.	0	.	140	58	0	.	0	.	0	.	0	.	0	.	17	.	237	49	171	59	0	.	45	108	0	0	127	.	11	100	0	.	0	.	0	.	0	.	0	.	99	67	146	65	53	100	0	.	0	.	0	.	93	73	112	93	428	35	14	70	0	.	0	.	23	74	54	70	109	69	177	62	206	81	266	45	152	77	334	61	169	67	0	.	0	.	79	71	0	.	0	.	0	.	0	.	0	.	95	67	0	.	0	.	0	.	0	.	690	26	851	23	759	24	8	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	13174	7
	41-50 cm	0	.	0	.	0	.	0	.	0	.	0	.	1843	20	110	74	0	.	0	.	0	.	0	.	0	.	0	.	17	.	92	62	98	52	23	100	0	.	63	72	713	32	298	37	1289	25	2114	19	852	23	0	.	-5	.	0	.	115	57	0	.	0	.	0	.	0	.	0	.	40	.	145	60	160	61	0	.	62	100	197	77	30	.	152	88	0	.	0	.	0	.	0	.	0	.	87	60	74	60	66	79	0	.	0	.	0	.	196	48	62	60	298	33	28	75	0	.	0	.	0	.	87	100	61	71	105	66	80	71	210	46	264	60	151	46	132	61	0	.	0	.	65	73	0	.	0	.	0	.	0	.	0	.	28	87	0	.	0	.	0	.	0	.	619	31	656	25	804	26	81	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	12563	7
	51-60 cm	0	.	0	.	0	.	0	.	0	.	0	.	1526	22	49	79	0	.	-8	100	0	.	0	.	0	.	0	.	28	.	-1	100	38	71	20	94	0	.	18	100	601	32	331	48	916	31	1252	19	487	27	0	.	0	.	0	.	33	73	0	.	0	.	0	.	0	.	0	.	0	.	138	50	87	61	0	.	0	.	216	70	6	.	207	80	0	.	0	.	0	.	0	.	0	.	91	71	15	100	98	100	0	.	0	.	0	.	219	60	99	59	123	56	17	100	0	.	0	.	22	100	22	100	128	76	35	88	44	100	92	71	94	60	16	100	159	60	0	.	0	.	90	82	0	.	0	.	0	.	0	.	0	.	36	100	0	.	0	.	0	.	0	.	359	33	414	28	653	31	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	8767	8
	61-70 cm	0	.	0	.	0	.	0	.	0	.	0	.	313	46	0	.	0	.	31	100	0	.	0	.	0	.	0	.	0	.	0	.	46	100	0	.	0	.	270	72	307	45	83	59	361	41	798	31	199	50	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	110	53	70	77	0	.	32	100	73	61	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	32	100	171	76	134	55	37	71	0	.	0	.	0	.	52	72	0	.	30	100	0	.	29	100	26	100	26	100	0	.	0	.	0	.	20	100	0	.	0	.	0	.	0	.	0	.	25	100	0	.	0	.	0	.	0	.	212	51	63	58	269	33	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	3820	13
	71-80 cm	0	.	0	.	0	.	0	.	0	.	0	.	167	53	0	.	0	.	88	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	92	100	100	59	117	75	75	71	494	33	94	61	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	31	100	0	.	118	100	34	100	0	.	77	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	34	100	0	.	0	.	0	.	27	100	0	.	90	78	0	.	0	.	0	.	24	100	0	.	40	100	0	.	0	.	0	.	27	100	33	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	232	42	57	71	84	75	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	2133	16
	81-90 cm	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	120	59	0	.	0	.	94	72	42	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	.	79	100	0	.	0	.	0	.	33	100	0	.	27	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	28	100	90	71	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	513	30
	91-100 cm	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	38	100	0	.	0	.	0	.	49	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	69	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	58	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	.	37	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	252	46
	>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	.	80	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	.	64	100	0	.	0	.	0	.	0	.	0	.	104	100	0	.	0	.	0	.	0	.	0	.	0	.	37	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	0	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	284	53
	total	0	.	0	.	0	.	0	.	0	.	0	.	6360	18	520	53	0	.	149	85	0	.	0	.	0	.	0	.	98	.	511	61	531	58	128	73	0	.	773	57	3112	27	1554	32	4418	21	8411	15	4400	19	0	.	41	.	0	.	542	46	0	.	0	.	0	.	31	.	0	.	87	.	923	42	621	51	0	.	295	71	666	57	213	.	474	76	0	.	0	.	0	.	0	.	0	.	346	48	496	60	278	78	0	.	0	.	0	.	769	40	548	50	1340	32	126	70	0	.	0	.	358	62	302	63	420	64	449	55	505	73	1090	39	638	56	694	49	638	53	0	.	0	.	280	72	0	.	0	.	0	.	0	.	0	.	245	58	0	.	0	.	0	.	0	.	3379	20	3122	19	3587	20	110	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	54581	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	50	54	4	.	0	.	74	46	149	44	389	30	601	21	969	16	349	29	1145	16	0	0	43	76	94	49	0	.	99	59	253	31	462	30	191	48	0	.	368	30	107	35	100	33	17	63	120	38	0	.	767	24	147	31	297	31	549	23	60	52	282	37	45	63	127	45	204	29	218	36	87	43	254	37	271	39	126	35	304	34	157	51	298	25	230	42	80	50	178	37	66	62	79	39	112	48	178	35	238	36	134	46	0	.	26	68	0	.	63	50	0	.	111	59	168	43	119	46	210	41	199	41	84	41	74	39	70	66	15	71	100	43	35	67	151	47	72	53	13	.	192	32	14	.	51	51	209	27	52	41	191	36	67	49	31	53	84	69	5	80	19	72	0	.	1	.	258	29	63	49	68	53	0	.	211	36	130	42	0	.	43	.	6	.	0	.	14277	4
	21-30 cm	158	49	0	.	0	.	143	45	567	32	1318	30	1203	16	1846	15	779	27	2070	16	21	100	62	71	178	45	0	.	64	69	414	38	905	27	522	35	0	.	897	30	244	34	280	37	5	100	178	50	0	.	1479	19	365	34	262	37	1045	22	103	52	339	32	200	44	167	39	444	31	436	37	102	48	620	31	643	28	348	43	550	28	225	41	1080	24	351	38	262	62	500	33	49	65	455	35	230	36	600	34	307	36	204	36	0	.	65	75	0	.	22	51	0	.	51	46	213	37	149	45	193	39	257	43	122	59	212	46	61	57	91	59	136	49	93	50	257	40	201	71	61	.	449	29	26	.	209	40	416	26	247	36	340	33	163	46	100	82	120	54	110	51	85	65	0	.	0	.	509	29	69	57	349	52	98	51	696	29	448	32	0	.	60	.	23	.	0	.	29919	4
	31-40 cm	188	59	0	.	0	.	335	46	807	30	1330	25	2059	18	3155	16	1527	23	2679	15	79	84	89	87	232	50	0	.	32	100	496	42	1072	26	1063	39	0	.	1101	25	299	42	319	32	54	68	85	69	0	.	2192	17	512	33	1125	30	1550	22	212	55	399	30	211	58	179	42	846	28	497	37	238	58	888	30	860	32	512	42	603	26	412	50	1209	25	400	43	507	41	467	34	163	54	448	32	296	33	822	29	634	35	331	46	0	.	106	58	0	.	55	75	0	.	52	59	124	52	114	50	91	44	138	60	149	52	191	45	51	66	90	79	119	51	128	48	225	51	346	43	211	.	574	27	21	.	166	46	455	28	194	45	642	31	252	36	59	72	236	51	166	54	251	96	0	.	0	.	437	29	320	49	190	38	293	50	1138	25	709	30	0	.	122	.	28	.	0	.	41956	4
	41-50 cm	132	57	0	.	0	.	135	52	745	32	1306	29	2454	18	4108	14	1655	24	1715	16	46	100	38	100	466	39	0	.	21	71	466	36	1052	27	468	36	0	.	1032	24	242	43	503	31	72	72	53	57	0	.	1696	18	471	35	777	32	1591	21	275	47	548	30	241	48	188	44	792	25	311	43	185	50	873	35	618	35	317	41	741	31	741	33	1288	22	188	58	432	34	482	39	448	49	495	33	344	35	1025	30	382	36	336	41	0	.	113	62	0	.	153	52	0	.	22	70	67	47	78	70	167	36	83	68	99	54	219	51	87	61	68	69	77	57	139	63	200	45	311	51	28	.	432	31	71	.	228	51	524	27	213	38	348	39	371	43	142	86	113	54	115	65	143	59	0	.	0	.	411	30	256	43	336	44	287	49	1032	30	442	40	0	.	25	.	74	.	0	.	39966	4
	51-60 cm	39	100	0	.	0	.	90	68	304	42	719	34	1851	20	2600	16	915	24	782	23	86	100	36	71	135	58	0	.	0	.	284	55	678	34	84	62	0	.	576	34	256	47	502	31	16	100	147	70	0	.	813	22	712	39	626	32	777	32	122	54	211	46	173	54	293	47	591	38	177	42	293	52	679	35	472	36	242	62	661	35	349	47	777	31	115	52	293	53	153	47	69	59	79	100	301	51	494	35	538	43	78	77	0	.	140	84	0	.	118	67	0	.	69	66	49	100	94	100	168	49	25	100	61	100	207	63	26	89	73	74	248	50	304	59	96	52	325	45	0	.	425	49	0	.	274	57	367	33	272	43	124	62	257	51	71	71	90	100	24	100	116	60	0	.	0	.	171	42	188	56	198	49	79	58	442	31	134	59	0	.	0	.	0	.	0	.	25424	5
	61-70 cm	0	.	64	.	0	.	38	100	106	78	34	100	652	28	1102	20	347	45	190	45	78	100	29	100	31	100	0	.	0	.	73	71	493	36	35	100	0	.	210	47	83	73	236	54	28	100	40	75	0	.	391	32	193	62	82	73	307	38	87	59	25	100	0	.	83	58	157	50	26	100	181	83	157	71	241	48	156	71	84	62	309	43	352	46	44	100	171	82	71	71	0	.	0	.	239	55	38	100	210	48	84	73	0	.	62	72	0	.	0	.	0	.	4	100	33	73	32	100	66	61	0	.	36	72	24	100	122	100	48	100	94	59	0	.	0	.	107	58	0	.	109	54	0	.	72	72	26	100	181	60	28	100	26	100	0	.	193	69	25	100	0	.	0	.	0	.	60	71	65	71	229	50	0	.	83	59	56	71	0	.	0	.	0	.	0	.	9341	7
	71-80 cm	0	.	0	.	0	.	0	.	82	72	0	.	157	60	814	29	90	71	96	71	0	.	0	.	0	.	0	.	0	.	59	80	74	71	0	.	0	.	142	54	0	.	36	100	65	100	94	100	0	.	75	73	0	.	0	.	116	70	80	71	88	71	58	100	176	64	81	71	0	.	0	.	58	100	0	.	75	100	50	75	156	52	331	67	46	100	0	.	0	.	0	.	0	.	92	100	47	100	92	58	0	.	0	.	0	.	0	.	152	100	0	.	0	.	37	100	0	.	0	.	46	100	0	.	0	.	0	.	0	.	47	100	38	100	0	.	97	100	0	.	98	100	0	.	0	.	113	59	41	100	0	.	84	100	0	.	0	.	101	100	0	.	0	.	0	.	52	75	42	100	47	100	0	.	80	71	46	100	0	.	0	.	0	.	0	.	4454	12
	81-90 cm	0	.	0	.	0	.	43	100	0	.	0	.	95	71	349	46	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	34	100	12	100	44	100	0	.	0	.	28	100	0	.	0	.	0	.	0	.	0	.	0	.	47	100	0	.	0	.	0	.	61	100	0	.	0	.	62	100	51	100	0	.	0	.	49	100	0	.	0	.	0	.	0	.	58	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	34	100	0	.	39	100	0	.	0	.	0	.	33	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	1040	23
	91-100 cm	0	.	0	.	0	.	0	.	0	.	0	.	77	100	0	.	0	.	53	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	44	100	0	.	0	.	0	.	0	.	0	.	74	100	0	.	56	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	35	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	38	100	0	.	0	.	0	.	0	.	0	.	0	.	36	100	0	.	0	.	0	.	70	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	38	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	519	33
	>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	.	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	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	68	100
	total	568	52	68	.	0	.	858	43	2760	29	5097	23	9147	14	14944	12	5663	19	8730	13	311	77	296	55	1136	38	0	.	215	63	2046	32	4736	22	2362	32	0	.	4326	21	1230	34	2012	26	270	61	761	41	0	.	7458	14	2428	30	3168	26	5936	19	939	42	1892	23	1002	42	1213	35	3284	22	1665	33	1087	47	3529	28	3165	25	1776	37	2992	23	2412	29	5386	20	1374	33	1745	35	1900	27	795	43	1555	30	1615	31	3204	26	2495	28	1167	35	0	.	511	64	0	.	562	51	0	.	309	40	729	36	586	48	896	29	748	36	551	44	928	43	418	59	455	63	821	39	777	48	930	37	1530	41	313	.	2311	25	132	.	999	42	2109	21	1200	36	1673	28	1220	37	403	64	836	49	546	54	614	68	0	.	1	.	1899	23	1004	40	1454	35	756	45	3682	23	1966	28	0	.	249	.	132	.	0	.	166964	3
submontane	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	12-20 cm	256	28	284	28	190	35	294	35	0	.	0	.	98	52	226	31	1234	17	0	.	55	48	152	42	144	46	23	.	47	62	83	64	0	.	175	40	0	.	0	.	49	65	24	59	0	.	0	.	0	.	279	31	184	59	252	33	39	76	20	62	0	.	80	47	22	.	0	.	0	.	0	.	23	100	23	71	117	55	29	75	77	65	0	.	307	29	35	51	61	53	134	41	97	45	31	74	0	.	2	100	115	40	221	32	242	34	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	72	91	0	.	42	73	43	76	58	73	0	.	42	69	43	88	11	84	115	49	34	72	0	.	108	60	115	53	92	61	105	52	87	78	0	.	27	53	0	.	0	.	80	55	14	74	10	83	131	41	16	84	172	37	114	39	133	41	151	38	0	.	7536	6
	21-30 cm	707	28	533	30	284	41	716	24	0	.	0	.	188	59	489	37	2424	14	0	.	133	50	324	44	353	40	7	.	205	56	246	46	0	.	492	32	0	.	0	.	98	67	106	64	0	.	0	.	0	.	763	26	436	35	693	27	55	81	71	44	0	.	118	57	55	.	0	.	0	.	0	.	28	100	62	77	343	52	89	71	71	74	0	.	667	35	156	46	185	48	208	43	306	46	11	100	0	.	92	71	147	49	385	36	364	32	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	69	71	0	.	81	72	55	58	70	71	0	.	107	51	15	100	55	82	285	56	112	91	0	.	125	49	195	50	350	44	138	48	66	71	0	.	213	75	0	.	0	.	30	60	62	81	53	59	268	37	35	100	280	42	256	37	360	43	278	37	0	.	16166	5
	31-40 cm	897	24	780	26	451	37	1500	23	0	.	0	.	473	42	595	31	3694	14	0	.	217	48	264	51	411	40	0	.	441	45	309	45	0	.	737	32	0	.	0	.	162	64	98	54	0	.	0	.	0	.	1111	24	640	29	1163	27	125	77	228	61	0	.	164	65	28	.	0	.	0	.	0	.	79	100	73	87	291	64	42	71	124	65	0	.	766	28	214	49	257	68	485	39	309	42	61	100	0	.	123	80	307	53	531	33	410	30	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	-2	100	0	.	40	76	76	72	74	68	0	.	158	54	57	100	52	91	254	48	96	61	0	.	85	79	93	69	334	47	213	59	55	80	0	.	200	76	0	.	0	.	18	73	96	77	180	61	583	41	108	92	442	37	620	34	416	35	599	33	0	.	23410	5
	41-50 cm	1032	31	977	30	280	36	1650	25	0	.	0	.	491	47	667	35	3699	15	0	.	230	53	118	50	206	59	40	.	245	54	319	52	0	.	627	35	0	.	0	.	133	66	131	63	0	.	0	.	0	.	970	25	570	33	895	27	96	84	183	64	0	.	109	64	0	.	0	.	0	.	0	.	29	100	98	89	205	57	74	100	111	87	0	.	603	29	657	41	74	61	508	47	148	55	30	100	0	.	65	72	416	49	759	32	409	33	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	1	100	0	.	6	100	57	59	40	71	0	.	193	51	0	.	94	100	99	55	88	87	0	.	112	61	49	72	140	62	35	73	80	71	0	.	213	55	0	.	0	.	57	68	38	100	227	52	569	40	54	100	606	41	513	36	554	34	582	34	0	.	22260	5
	51-60 cm	538	35	982	31	206	43	799	31	0	.	0	.	266	50	394	38	2180	17	0	.	273	46	123	61	156	55	23	.	182	54	112	54	0	.	304	38	0	.	0	.	97	74	118	61	0	.	0	.	0	.	367	35	390	42	457	40	80	76	35	71	0	.	30	152	0	.	0	.	0	.	0	.	0	.	51	100	51	100	0	.	74	61	0	.	329	40	323	56	0	.	246	54	17	100	0	.	0	.	0	.	220	49	443	36	378	35	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	33	100	0	.	0	.	67	70	25	100	0	.	52	71	0	.	0	.	97	50	21	100	0	.	65	100	42	72	0	.	33	74	32	75	0	.	54	74	0	.	0	.	152	55	0	.	39	100	139	45	21	100	366	39	242	42	398	50	269	34	0	.	12388	6
	61-70 cm	378	43	195	54	112	59	133	59	0	.	0	.	72	71	171	54	860	25	0	.	119	77	73	100	24	100	36	.	68	71	72	71	0	.	127	64	0	.	0	.	31	100	0	.	0	.	0	.	0	.	151	51	56	71	174	63	33	100	0	.	0	.	29	100	0	.	0	.	0	.	0	.	0	.	0	.	130	79	0	.	138	100	0	.	65	71	145	50	0	.	34	100	0	.	0	.	0	.	0	.	62	70	135	61	292	49	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	31	100	0	.	0	.	0	.	132	71	0	.	0	.	62	100	26	100	0	.	0	.	0	.	0	.	0	.	23	100	0	.	0	.	0	.	0	.	39	80	0	.	0	.	94	74	0	.	181	53	128	62	95	59	141	64	0	.	4865	10
	71-80 cm	36	100	43	100	44	100	149	59	0	.	0	.	0	.	209	51	439	33	0	.	59	100	0	.	0	.	0	.	0	.	86	71	0	.	94	71	0	.	0	.	0	.	50	100	0	.	0	.	0	.	0	.	74	71	38	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	38	100	39	100	152	50	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	18	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	36	100	0	.	0	.	0	.	0	.	0	.	0	.	35	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	102	71	39	100	41	100	39	100	0	.	1861	15
	81-90 cm	0	.	0	.	68	100	0	.	0	.	0	.	0	.	92	72	255	70	0	.	81	100	57	100	0	.	0	.	0	.	49	100	0	.	125	71	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	.	64	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	41	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	53	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	40	100	0	.	0	.	0	.	963	28
	91-100 cm	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	34	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	.	72	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	68	100	0	.	0	.	0	.	0	.	174	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	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	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	3843	21	3795	23	1634	28	5241	20	0	.	0	.	1588	42	2842	26	14785	11	0	.	1167	38	1111	36	1294	36	128	.	1187	44	1275	39	0	.	2716	28	0	.	0	.	570	54	527	53	0	.	0	.	0	.	3640	21	2387	27	3672	23	428	72	537	54	0	.	530	52	105	.	0	.	0	.	0	.	158	100	308	78	1138	52	234	74	594	60	0	.	2801	23	1528	38	577	52	1615	36	876	38	134	86	0	.	281	73	1305	38	2554	26	2318	25	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	193	71	0	.	201	71	298	62	267	67	0	.	685	52	114	71	212	80	1001	43	376	66	0	.	496	50	494	49	916	43	524	47	378	56	0	.	707	63	0	.	0	.	376	48	211	72	510	50	1783	33	234	82	2218	31	1951	29	1998	31	2060	28	0	.	89623	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	.	183	52	0	.	0	.	0	.	0	.	184	47	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	.	6	.	18	.	39	46	65	56	219	43	341	30	663	22	97	53	192	55	337	27	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	50	76	0	.	0	.	48	.	0	.	0	.	0	.	141	44	43	48	32	48	0	.	0	.	0	.	0	.	0	.	26	72	0	.	0	.	0	.	2685	10
	21-30 cm	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	77	49	0	.	0	.	0	.	0	.	143	50	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	.	0	.	12	.	43	86	92	67	101	43	276	33	551	26	61	54	76	39	371	33	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	18	73	0	.	0	.	11	.	0	.	0	.	0	.	160	46	93	53	42	67	0	.	0	.	0	.	0	.	0	.	44	92	0	.	0	.	0	.	2175	11
	31-40 cm	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	44	82	0	.	0	.	0	.	0	.	55	59	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	.	12	.	0	.	11	100	58	69	85	62	163	41	287	38	38	54	44	63	209	33	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	92	46	58	51	24	72	0	.	0	.	0	.	0	.	0	.	135	92	0	.	0	.	0	.	1338	16
	41-50 cm	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	85	95	0	.	0	.	0	.	0	.	42	51	43	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	.	57	.	0	.	8	100	16	71	31	100	50	47	125	49	58	48	66	70	121	42	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	5	100	0	.	0	.	0	.	0	.	0	.	0	.	81	89	0	.	27	72	0	.	0	.	0	.	0	.	0	.	45	73	0	.	0	.	0	.	860	19
	51-60 cm	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	46	100	0	.	0	.	0	.	0	.	23	67	0	.	0	.	0	.	0	.	0	.	0	.	0	.	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	12	100	53	60	51	50	0	.	75	49	56	51	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	18	100	25	100	40	100	0	.	0	.	0	.	0	.	0	.	21	100	0	.	0	.	0	.	434	22
	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	.	26	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	.	22	.	0	.	0	.	0	.	0	.	17	100	30	100	0	.	35	58	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	18	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	147	37
	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	.	99	100	0	.	0	.	0	.	90	62	0	.	0	.	65	62	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	19	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	273	45
	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	.	29	100	0	.	0	.	0	.	83	77	0	.	0	.	6	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	.	118	60
	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	.	32	100	0	.	0	.	47	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	.	80	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	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	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	100	0	.	0	.	0	.	0	.	189	100	0	.	133	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	.	364	58
	total	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	435	51	0	.	0	.	0	.	0	.	447	41	96	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	.	75	.	52	.	271	71	246	60	449	38	883	30	1900	20	473	48	454	38	1379	27	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	72	73	0	.	0	.	59	.	0	.	0	.	0	.	491	40	219	48	202	50	0	.	0	.	0	.	0	.	0	.	272	80	0	.	0	.	0	.	8473	9
total	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	12-20 cm	306	25	288	27	190	35	368	29	149	44	389	30	1166	13	1220	14	1583	15	1153	16	55	48	195	37	238	34	23	.	153	43	410	25	544	28	371	31	183	52	392	28	330	20	310	26	358	22	969	15	904	15	1046	19	351	34	548	23	684	20	81	42	282	37	126	38	155	39	204	29	270	33	226	29	353	30	294	37	250	31	382	28	247	39	328	24	537	24	114	38	239	31	200	34	175	30	160	37	289	39	243	35	249	31	221	32	274	30	54	43	205	23	145	32	340	34	509	24	782	20	366	28	425	31	456	22	164	44	112	47	236	37	162	34	109	45	246	44	114	42	55	72	203	30	129	45	84	42	209	27	210	37	306	30	186	37	184	40	171	52	5	80	46	43	874	18	696	17	777	18	80	41	79	47	131	41	228	34	303	28	140	35	175	39	158	36	0	.	30625	2
	21-30 cm	865	24	533	30	284	41	859	21	567	32	1318	30	2844	12	2472	14	3202	13	2077	16	154	45	385	38	531	31	7	.	298	42	816	28	1032	25	1036	23	77	49	967	29	1104	20	763	24	870	25	1893	15	2098	15	2242	15	827	24	954	22	1261	20	175	36	339	32	318	35	246	36	444	31	511	33	322	34	850	25	705	26	722	32	787	22	333	34	1158	23	1018	26	417	42	685	27	257	37	761	28	308	29	750	31	424	31	351	29	385	36	429	30	69	45	296	34	369	36	175	30	489	24	700	23	369	26	392	30	541	27	372	32	197	51	534	32	225	34	286	33	342	34	308	50	76	83	529	26	312	52	322	41	416	26	390	28	535	28	561	31	248	43	186	43	110	51	298	56	1394	16	1185	17	1556	17	149	45	402	45	366	30	732	28	728	25	300	34	419	39	301	35	0	.	62212	2
	31-40 cm	1086	22	780	26	451	37	1836	21	807	30	1330	25	5208	12	4005	14	5221	12	2702	15	297	41	353	44	643	31	0	.	489	41	994	28	1212	24	1857	26	44	82	1221	23	1713	19	799	20	1472	21	2637	16	3434	13	3302	14	1152	22	2288	20	1815	20	439	41	399	30	375	43	206	39	846	28	544	34	549	35	1198	25	933	31	848	34	743	24	664	38	1237	25	1166	23	721	32	724	33	648	32	757	25	502	27	968	26	809	30	638	35	531	33	527	26	121	59	372	37	607	28	150	41	286	32	401	31	223	27	247	39	466	27	367	38	305	58	487	35	347	41	564	39	400	40	504	34	268	81	706	24	275	45	261	37	455	28	280	39	735	28	705	27	272	49	291	44	166	54	451	63	1653	15	1466	17	1639	18	425	41	370	36	876	32	1246	24	1151	23	755	32	538	35	627	31	0	.	87578	2
	41-50 cm	1164	28	977	30	280	36	1784	23	745	32	1306	29	5659	12	4928	13	5354	12	1715	16	276	47	156	45	672	32	40	.	283	47	878	28	1150	25	1119	25	85	95	1201	21	1623	19	1011	21	1953	18	2762	15	2388	14	2666	14	1035	24	1672	20	1801	19	457	38	548	30	350	38	188	44	792	25	385	37	416	35	1087	29	716	32	599	31	1123	27	882	30	1440	22	791	26	1089	28	556	35	956	34	643	29	485	28	1099	28	512	30	752	33	759	32	580	28	305	37	497	26	380	28	81	50	118	34	203	40	311	30	259	44	281	30	335	40	258	43	322	35	409	41	353	33	374	33	504	37	28	100	591	29	170	53	316	44	524	27	330	32	397	35	573	32	177	71	193	43	115	65	355	40	1509	17	1311	21	1820	17	376	38	563	34	856	31	1086	29	1048	29	558	34	579	33	656	32	0	.	83004	2
	51-60 cm	577	33	982	31	206	43	889	28	304	42	719	34	3945	13	3058	15	3096	13	774	23	360	42	159	50	291	40	23	.	210	48	395	42	716	32	408	32	46	100	642	31	1404	21	1047	23	1303	25	1731	16	1615	18	1180	19	1102	29	1084	25	890	29	157	45	211	46	203	51	293	47	591	38	214	39	443	38	790	31	523	34	314	51	939	30	429	39	977	30	444	32	616	39	153	47	315	44	95	84	469	39	509	34	636	40	298	42	443	36	518	34	277	50	462	37	158	45	98	51	102	57	146	67	274	37	138	38	245	48	275	50	130	51	257	49	444	33	350	52	255	42	377	40	0	.	516	43	97	50	294	53	367	33	336	40	166	50	301	45	104	54	122	76	24	100	170	47	1044	19	879	21	1312	19	188	56	237	44	217	36	462	30	500	33	263	40	398	50	269	34	0	.	51988	3
	61-70 cm	378	43	259	47	112	59	171	51	106	78	34	100	1233	20	1273	19	1208	22	221	42	197	61	102	77	55	71	36	.	68	71	145	50	538	34	162	55	0	.	508	43	627	28	319	43	545	30	1168	24	521	27	542	27	249	50	256	49	340	35	87	59	25	100	29	100	83	58	157	50	54	71	321	51	253	50	241	48	345	45	193	38	447	43	352	46	108	58	316	50	71	71	34	100	0	.	297	48	38	100	210	48	146	52	135	61	353	42	75	59	217	63	134	55	41	64	33	73	50	74	139	42	90	59	71	46	80	58	144	86	107	59	120	51	26	100	35	100	240	47	0	.	128	48	62	100	97	59	26	100	181	60	28	100	51	71	0	.	216	63	25	100	0	.	715	31	63	58	587	25	65	71	229	50	94	74	83	59	237	44	128	62	95	59	141	64	0	.	20526	5
	71-80 cm	36	100	43	100	44	100	149	59	82	72	0	.	373	36	1023	25	529	30	184	60	59	100	0	.	0	.	0	.	0	.	145	53	74	71	94	71	0	.	266	47	262	43	226	48	202	45	689	29	262	33	75	73	74	71	38	100	116	70	80	71	88	71	58	100	176	64	81	71	0	.	0	.	89	74	0	.	194	72	84	60	156	52	408	57	46	100	0	.	0	.	0	.	0	.	92	100	47	100	126	50	38	100	39	100	152	50	60	71	251	72	90	78	0	.	37	100	90	62	64	73	46	100	105	54	47	73	30	100	0	.	74	73	72	71	0	.	97	100	0	.	98	100	36	100	0	.	113	59	41	100	0	.	84	100	0	.	35	100	101	100	0	.	673	26	139	46	155	49	42	100	47	100	0	.	80	71	148	58	39	100	41	100	39	100	0	.	9975	7
	81-90 cm	0	.	0	.	68	100	43	100	0	.	0	.	95	71	440	39	255	70	0	.	81	100	57	100	0	.	0	.	0	.	49	100	0	.	125	71	0	.	150	51	42	100	34	100	169	48	116	58	68	72	0	.	66	71	0	.	0	.	0	.	0	.	0	.	0	.	47	100	0	.	0	.	0	.	61	100	0	.	21	100	62	100	51	100	64	100	0	.	49	100	0	.	0	.	0	.	0	.	58	100	0	.	41	100	0	.	0	.	49	72	0	.	0	.	0	.	83	77	79	100	0	.	6	100	0	.	33	100	34	100	27	100	39	100	33	100	0	.	0	.	33	100	53	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	70	74	64	71	90	71	0	.	0	.	0	.	0	.	0	.	40	100	0	.	0	.	0	.	3048	14
	91-100 cm	0	.	0	.	0	.	0	.	0	.	0	.	77	100	0	.	0	.	53	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	34	100	0	.	38	100	0	.	0	.	99	72	49	100	0	.	44	100	0	.	0	.	0	.	0	.	0	.	74	100	0	.	56	100	0	.	0	.	0	.	0	.	0	.	93	79	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	35	100	0	.	0	.	72	100	58	100	0	.	0	.	0	.	38	100	32	100	0	.	0	.	47	78	0	.	0	.	36	100	0	.	0	.	0	.	70	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	92	73	37	100	0	.	0	.	38	100	0	.	0	.	68	100	0	.	0	.	0	.	0	.	1239	21
	>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	.	112	77	50	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	68	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	64	100	41	100	0	.	0	.	0	.	0	.	293	74	0	.	133	66	0	.	0	.	0	.	0	.	37	100	65	100	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	.	0	.	893	32
	total	4411	19	3863	22	1634	28	6099	18	2760	29	5097	23	20601	10	18418	10	20447	9	8878	12	1477	34	1407	30	2429	26	128	.	1500	36	3832	23	5266	21	5206	21	435	51	5385	19	7103	16	4510	18	6971	16	12126	11	11339	11	11098	11	4856	20	6841	17	6908	17	1476	33	1892	23	1533	32	1348	33	3284	22	1977	29	2278	29	4621	23	3473	24	3272	28	4367	20	3220	25	5951	19	4175	19	3274	26	2477	24	2410	28	2431	23	2314	24	3700	24	3054	25	2472	26	2554	26	2905	23	1083	32	2391	23	1883	25	886	25	1612	23	2486	19	2117	21	1598	23	2351	22	1639	30	1209	40	2014	29	1808	28	1836	29	1749	28	2214	33	427	76	2803	23	1133	39	1375	35	2109	21	1768	28	2166	24	2461	25	986	37	1214	38	546	54	1321	46	8055	12	5842	14	7936	13	1324	33	1964	29	2540	27	3917	22	4184	21	2224	28	2246	30	2191	27	0	.	351089	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. 2281752. Birmensdorf, Swiss Federal Research Institute WSL

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