Selection from the list of topics

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

1. What do the numbers stand for?

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

Example 1: Estimated value and standard error

NFI5

volume of deadwood (stemwood)
ownership (2 categories)

regional demarcation: production region

unit: m³/ha

evaluation area: accessible forest without shrub forest

grid: 1.4 km grid, subgrids 1-5

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

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

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2. What is the purpose of the standard error?

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

The statistical certainty is:

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

Example 2: Calculating confidence intervals

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

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

Procedure

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

Answer

			Step 1	Step 2

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

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

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

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

Data: see example 2

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

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

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3. When are two results statistically different?*

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

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

Example 4: Interpretation of two results from the same inventory

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

	case 2						case 1

case 1

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

Procedure

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

Answer

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

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

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

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

Case 2

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

Procedure

See case 1.

Answer

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

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

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

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

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

Example 5: Interpretation of two results from different inventories

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

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

Procedure

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

Answer

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

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

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

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

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

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

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

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

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

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

Procedure

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

Answer

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

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

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

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

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

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

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

Procedure

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

Answer

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

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

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

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

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

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

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

Example 8: Standard error and combination of variable expressions

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

The standard error increases as the level of detail increases.

Large standard errors are to be expected if:

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

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

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

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5. Two types of changes?

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

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

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

The results are:

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

Example 9: : Additivity/non-additivity of changes

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

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

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

Example 10: Average number of years per domain

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

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

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

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

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

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

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

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

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

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

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NFI4
growing stock (stemwood)
altitudinal vegetation belts (NaiS; 6 classes) · diameter at breast height (10 classes)
regional demarcation: forest district (2024)
unit: 1000 m³
evaluation area: accessible forest without shrub forest
grid: 1.4-km grid
state 2009/17
		forest district (2024)
		AG01		AG02		AG03		AG04		AI01		AR01		BE01		BE02		BE03		BE04		BSBL01		BSBL02		BSBL03		BSBL04		FR01		FR02		FR03		FR04		GE01		GL01		GR01		GR02		GR03		GR04		GR05		JU01		LU01		LU02		LU03		NE01		NE02		NE03		NE04		NE06		NW01		OW01		OW02		SG01		SG02		SG03		SG04		SG05		SH01		SO01		SO02		SO03		SO04		SZ01		SZ02		SZ03		TG01		TG02		TG03		TI01		TI02		TI03		TI04		TI05		TI06		TI07		TI08		TI09		UR01		UR02		UR03		VD02		VD03		VD04		VD05		VD06		VD07		VD08		VD09		VD11		VD12		VD14		VD15		VD16		VD18		VD20		VD22		VS01		VS02		VS03		ZG01		ZH01		ZH02		ZH03		ZH04		ZH05		ZH06		ZH07		lakes		Switzerland
altitudinal vegetation belts (NaiS; 6 classes)	diameter at breast height (10 classes)	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%
n/a	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	12-20 cm	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	21-30 cm	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	31-40 cm	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	41-50 cm	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	51-60 cm	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	61-70 cm	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	71-80 cm	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	81-90 cm	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	91-100 cm	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	>100 cm	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	total	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.
upper subalpine	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	12-20 cm	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	10	73	1	100	2	75	33	26	314	16	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	1	83	25	42	18	71	16	98	0	.	0	.	8	73	5	.	1	.	0	.	0	.	6	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	126	27	60	29	18	45	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	645	11
	21-30 cm	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	15	58	29	100	4	100	55	41	537	17	0	.	0	.	0	.	0	.	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	100	34	58	32	61	-2	100	0	.	0	.	22	50	2	.	0	.	0	.	0	.	8	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	307	26	116	28	44	47	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	1212	11
	31-40 cm	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	40	66	4	100	8	100	164	34	687	18	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	7	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	7	72	7	140	39	53	0	.	0	.	0	.	25	61	0	.	0	.	0	.	0	.	22	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	269	23	216	35	66	47	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	1560	11
	41-50 cm	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	15	80	8	100	0	.	168	29	693	18	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	10	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	61	48	25	69	0	.	0	.	0	.	25	100	0	.	11	.	0	.	0	.	2	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	380	23	148	32	25	59	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	1571	11
	51-60 cm	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	16	100	0	.	177	42	543	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	.	6	100	19	72	27	58	12	100	0	.	0	.	8	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	285	26	81	38	23	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	1196	14
	61-70 cm	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	29	100	0	.	0	.	56	69	283	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	.	45	73	10	100	0	.	0	.	0	.	26	71	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	135	31	87	41	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	671	16
	71-80 cm	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	16	100	0	.	0	.	64	51	147	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	.	15	100	0	.	12	100	0	.	0	.	0	.	19	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	200	32	27	71	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	500	19
	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	.	57	59	130	47	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	15	100	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	.	46	59	11	100	14	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	307	28
	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	.	55	74	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	38	72	20	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	113	47
	>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	.	19	100	48	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	.	46	71	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	113	45
	total	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	125	66	58	100	13	92	793	26	3438	14	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	17	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	39	66	206	38	163	42	59	65	0	.	0	.	133	52	7	.	12	.	0	.	0	.	39	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	1831	18	766	24	189	43	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	7889	8
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	.	218	20	0	0	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	17	.	0	.	0	.	28	51	136	24	67	38	219	26	279	23	387	20	0	.	0	.	0	.	4	100	0	.	0	.	0	.	0	.	0	.	37	78	30	63	40	65	0	.	12	100	45	42	8	.	6	.	0	.	0	.	0	.	0	.	0	.	7	72	0	.	0	.	0	.	0	.	0	.	27	38	80	37	37	44	8	100	0	.	0	.	61	37	17	77	25	88	0	.	4	72	30	68	9	76	9	50	2	74	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	4	.	0	.	0	.	0	.	0	.	242	20	145	29	119	28	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	2359	7
	21-30 cm	0	.	0	.	0	.	0	.	0	.	0	.	583	19	8	71	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	26	.	0	.	0	.	76	46	284	30	203	33	534	23	578	20	771	16	0	.	0	.	0	.	28	88	0	.	0	.	0	.	0	.	0	.	86	64	43	91	81	58	0	.	16	100	62	50	7	.	7	.	0	.	0	.	0	.	0	.	0	.	4	100	0	.	0	.	0	.	0	.	0	.	18	100	152	37	75	53	27	74	0	.	0	.	109	43	42	81	26	100	10	100	20	65	25	67	29	58	0	0	24	77	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	4	.	0	.	0	.	0	.	0	.	465	22	467	23	397	26	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	5287	6
	31-40 cm	0	.	0	.	0	.	0	.	0	.	0	.	1066	17	20	81	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	28	.	0	.	0	.	83	87	566	24	246	36	576	24	932	19	1007	16	0	.	0	.	0	.	17	71	0	.	0	.	0	.	0	.	0	.	42	79	59	58	111	45	0	.	7	100	182	52	0	.	10	.	0	.	0	.	0	.	0	.	0	.	31	61	0	.	0	.	0	.	0	.	0	.	98	43	183	36	126	43	5	100	0	.	0	.	61	44	16	55	22	100	0	.	86	62	21	73	44	59	51	54	7	73	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	19	.	0	.	0	.	0	.	0	.	666	21	693	21	633	22	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	7719	6
	41-50 cm	0	.	0	.	0	.	0	.	0	.	0	.	1061	19	46	60	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	154	43	578	25	274	29	809	22	1070	18	1431	16	0	.	0	.	0	.	35	100	0	.	0	.	0	.	0	.	0	.	34	62	36	51	101	52	0	.	17	100	103	55	0	.	0	.	0	.	0	.	0	.	0	.	0	.	40	100	0	.	0	.	0	.	0	.	0	.	80	49	136	35	132	41	6	100	0	.	0	.	154	44	45	54	0	0	4	100	41	82	18	77	67	90	45	49	65	75	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	17	.	0	.	0	.	0	.	0	.	822	21	653	21	642	23	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	8713	6
	51-60 cm	0	.	0	.	0	.	0	.	0	.	0	.	769	20	49	71	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	140	45	665	26	166	37	704	19	781	20	1494	25	0	.	0	.	0	.	9	100	0	.	0	.	0	.	0	.	0	.	51	77	7	100	50	57	0	.	13	100	59	48	0	.	0	.	0	.	0	.	0	.	0	.	0	.	28	75	0	.	0	.	0	.	0	.	0	.	171	38	261	33	93	45	0	.	0	.	0	.	133	44	13	74	0	.	23	100	44	71	9	100	70	87	59	51	71	86	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	18	.	0	.	0	.	0	.	0	.	812	20	670	25	567	25	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	7999	7
	61-70 cm	0	.	0	.	0	.	0	.	0	.	0	.	381	28	28	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	63	62	246	37	71	43	443	28	390	26	699	33	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	11	100	45	75	25	71	0	.	11	100	48	51	0	.	0	.	0	.	0	.	0	.	0	.	0	.	48	77	0	.	0	.	0	.	0	.	0	.	51	51	94	50	60	47	0	.	0	.	0	.	40	78	13	100	0	.	0	0	25	71	0	.	41	64	16	100	58	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	7	.	0	.	0	.	0	.	0	.	546	27	253	29	221	34	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	3930	10
	71-80 cm	0	.	0	.	0	.	0	.	0	.	0	.	329	32	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	86	61	402	40	38	71	144	45	189	44	167	40	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	15	100	17	100	0	.	0	.	15	100	14	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	50	100	0	.	0	.	0	.	0	.	0	.	114	48	37	71	40	71	0	.	0	.	0	.	54	60	13	100	0	.	14	100	0	.	0	.	13	100	67	51	47	75	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	491	29	47	58	145	45	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	2548	12
	81-90 cm	0	.	0	.	0	.	0	.	0	.	0	.	28	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	31	71	35	100	21	100	142	45	60	58	73	60	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	49	100	0	.	0	.	19	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	37	100	65	77	60	74	0	.	0	.	0	.	18	100	0	.	0	.	0	.	0	.	0	.	52	77	0	.	24	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	218	36	36	71	22	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	992	17
	91-100 cm	0	.	0	.	0	.	0	.	0	.	0	.	20	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	43	71	50	100	20	100	39	100	0	.	80	80	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	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	.	57	72	0	0	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	335	33
	>100 cm	0	.	0	.	0	.	0	.	0	.	0	.	22	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	64	100	0	.	0	.	72	71	43	100	21	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	22	100	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	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	274	38
	total	0	.	0	.	0	.	0	.	0	.	0	.	4477	16	152	60	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	71	.	0	.	0	.	768	38	2963	21	1107	25	3684	16	4324	15	6130	15	0	.	0	.	0	.	94	87	0	.	0	.	0	.	0	.	0	.	275	52	237	52	459	37	0	.	91	71	553	38	16	.	23	.	0	.	0	.	0	.	0	.	0	.	208	65	0	.	0	.	0	.	0	.	0	.	624	32	1030	26	622	37	46	71	0	.	0	.	629	30	159	49	73	96	50	92	219	63	102	69	325	62	246	40	297	74	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	69	.	0	.	0	.	0	.	0	.	4320	16	2963	18	2747	19	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	40155	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	.	7	.	0	.	434	15	19	69	0	.	2	100	0	.	0	.	0	.	0	.	4	100	50	41	35	45	3	71	0	.	37	48	124	27	133	24	602	20	667	16	408	22	0	.	14	74	0	.	66	43	0	.	0	.	0	.	0	.	0	.	16	52	85	38	23	49	0	.	15	71	25	44	8	69	5	69	0	.	0	.	0	.	0	.	0	.	24	54	77	38	12	56	0	.	0	.	0	.	170	34	81	39	130	29	7	59	0	.	0	.	73	30	11	62	32	62	22	57	23	50	106	31	34	59	59	41	63	51	0	.	0	.	3	71	0	.	0	.	3	83	0	.	0	.	9	64	0	.	0	.	0	.	0	.	505	15	504	19	366	21	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	5095	5
	21-30 cm	0	.	0	.	0	.	0	.	13	.	0	.	775	17	27	114	0	.	0	.	0	.	0	.	0	.	0	.	3	107	172	53	115	43	13	78	0	.	64	71	211	29	389	25	673	17	1086	14	720	19	0	.	56	71	0	.	102	40	0	.	0	.	0	.	0	.	0	.	57	58	314	33	78	42	0	.	34	65	56	56	17	71	3	100	0	.	0	.	0	.	0	.	0	.	14	60	114	42	9	73	0	.	0	.	0	.	145	34	180	36	194	25	26	50	0	.	0	.	157	32	40	57	49	67	22	103	81	56	190	34	49	45	115	48	237	56	0	.	0	.	0	.	0	.	0	.	-3	100	0	.	7	100	31	73	0	.	0	.	0	.	0	.	924	16	895	18	695	20	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	9152	5
	31-40 cm	0	.	0	.	0	.	0	.	10	.	0	.	1155	16	162	50	0	.	6	100	0	.	0	.	0	.	0	.	29	71	214	43	204	67	40	72	0	.	3	127	571	24	530	25	683	19	1650	14	1259	18	0	.	60	75	0	.	158	35	0	.	0	.	0	.	0	.	0	.	60	62	300	32	113	46	0	.	68	75	99	51	36	76	0	0	0	.	0	.	0	.	0	.	0	.	78	48	111	53	32	61	0	.	0	.	0	.	201	37	224	41	309	34	45	55	0	.	0	.	206	32	38	66	81	63	56	60	144	51	316	38	65	53	238	44	176	41	0	.	0	.	21	100	0	.	0	.	33	100	0	.	11	100	53	78	0	.	0	.	0	.	0	.	1226	15	784	18	720	21	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	12574	5
	41-50 cm	0	.	0	.	0	.	0	.	8	.	0	.	1441	16	137	43	0	.	0	.	0	.	0	.	0	.	0	.	119	72	156	47	213	39	57	71	0	.	109	54	855	23	489	26	754	21	2101	13	1225	17	0	.	54	72	0	.	150	38	0	.	0	.	0	.	0	.	0	.	20	58	260	34	135	40	0	.	74	71	103	62	63	73	110	58	0	.	0	.	0	.	0	.	0	.	136	52	240	37	64	66	0	.	0	.	0	.	50	42	226	36	557	29	38	53	0	.	0	.	146	35	33	68	28	79	126	53	152	62	306	37	157	74	274	35	186	43	0	.	0	.	17	100	0	.	0	.	42	72	23	100	48	99	85	45	0	.	0	.	0	.	0	.	938	17	802	21	708	20	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	14015	5
	51-60 cm	0	.	0	.	0	.	0	.	0	.	0	.	1565	18	91	48	0	.	6	100	0	.	0	.	0	.	0	.	55	71	59	61	265	44	94	72	0	.	75	50	834	26	575	27	1096	21	1671	15	759	22	0	.	-3	100	0	.	107	44	0	.	0	.	0	.	0	.	0	.	36	77	247	43	147	38	0	.	22	100	55	74	11	100	114	71	0	.	0	.	0	.	0	.	0	.	72	53	189	38	33	100	0	.	0	.	0	.	81	44	230	34	293	35	26	75	0	.	0	.	167	32	44	71	56	62	96	62	48	67	180	38	194	50	204	39	273	37	0	.	0	.	20	100	0	.	0	.	31	77	31	78	39	73	19	77	0	.	0	.	0	.	0	.	1144	18	678	21	787	20	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	12814	5
	61-70 cm	0	.	0	.	0	.	0	.	0	.	0	.	795	20	87	68	0	.	0	.	0	.	0	.	0	.	0	.	20	100	0	.	89	48	56	61	0	.	104	69	420	31	244	40	483	24	1188	16	296	36	0	.	0	.	0	.	29	71	0	.	0	.	0	.	0	.	0	.	15	100	127	47	40	58	0	.	18	100	99	47	7	100	119	74	0	.	0	.	0	.	0	.	0	.	74	67	49	79	11	100	0	.	0	.	0	.	124	61	99	47	267	36	11	100	0	.	0	.	48	50	15	100	116	77	23	100	63	63	110	56	104	57	140	46	194	62	7	.	0	.	41	100	0	.	0	.	0	.	37	77	33	72	23	72	0	.	0	.	0	.	0	.	619	26	348	27	457	29	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	7250	7
	71-80 cm	0	.	0	.	0	.	0	.	0	.	0	.	427	25	32	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	34	100	59	83	0	.	200	53	174	36	263	38	472	27	758	24	151	34	0	.	0	.	0	.	21	100	0	.	0	.	0	.	0	.	0	.	0	.	98	59	67	72	0	.	0	.	16	100	49	100	45	100	0	.	0	.	0	.	0	.	0	.	22	100	31	100	0	.	0	.	0	.	0	.	98	52	108	62	111	49	15	100	0	.	0	.	0	0	30	71	30	100	37	71	120	87	184	64	46	77	167	51	71	78	0	.	0	.	25	100	0	.	0	.	0	.	0	.	0	.	16	100	0	.	0	.	0	.	0	.	580	35	193	44	417	41	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	5167	9
	81-90 cm	0	.	0	.	0	.	0	.	0	.	0	.	241	44	31	100	0	.	58	100	0	.	0	.	0	.	0	.	0	.	0	.	23	100	0	.	0	.	18	100	133	64	195	42	139	46	364	31	65	62	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	34	100	0	.	0	.	0	.	0	.	50	71	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	55	71	84	60	0	0	0	.	0	.	0	.	0	.	23	100	0	.	49	100	0	.	20	100	118	50	48	71	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	153	54	148	43	86	62	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	2135	13
	91-100 cm	0	.	0	.	0	.	0	.	0	.	0	.	56	71	0	.	0	.	36	100	0	.	0	.	0	.	0	.	0	.	0	.	27	100	0	.	0	.	59	71	0	.	0	.	37	100	83	64	63	71	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	.	0	.	0	.	20	100	0	.	38	100	0	.	0	.	0	.	87	71	0	.	0	.	0	.	25	100	37	100	0	.	69	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	70	72	88	59	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	824	21
	>100 cm	0	.	0	.	0	.	0	.	0	.	0	.	54	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	28	100	40	100	290	78	43	100	193	53	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	43	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	87	100	58	100	0	.	0	.	0	.	0	.	40	100	0	.	32	100	0	.	0	.	43	100	0	.	21	100	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	.	998	29
	total	0	.	0	.	0	.	0	.	38	.	0	.	6943	13	585	44	0	.	108	93	0	.	0	.	0	.	0	.	232	71	650	42	1005	38	323	58	0	.	697	45	3360	19	3108	20	4982	14	9762	10	4945	14	0	.	181	72	0	.	632	31	0	.	0	.	0	.	0	.	0	.	238	51	1430	28	676	36	0	.	231	69	502	41	191	69	395	56	0	.	0	.	0	.	0	.	0	.	422	42	811	33	161	58	0	.	0	.	0	.	974	27	1260	28	1983	22	168	47	0	.	0	.	925	26	211	55	446	50	382	54	707	43	1471	29	669	45	1404	29	1247	33	7	.	0	.	127	70	0	.	0	.	106	71	91	82	137	74	236	49	0	.	0	.	0	.	0	.	6158	12	4440	15	4265	15	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	70025	3
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	26	51	0	.	4	63	39	45	117	38	185	26	734	15	723	12	313	23	701	13	0	.	20	46	101	28	0	.	25	50	95	30	308	22	195	35	0	.	237	28	181	27	145	26	18	103	157	30	0	.	739	14	217	26	207	29	333	16	45	60	188	24	37	40	85	28	246	35	110	32	76	39	252	27	106	32	111	40	242	24	166	29	184	21	74	41	110	33	128	34	36	54	91	29	352	24	134	34	154	30	108	32	0	.	58	75	0	.	78	41	0	.	212	27	180	26	75	30	334	20	274	26	188	27	115	35	86	52	28	51	91	33	63	47	222	27	93	40	10	71	236	25	28	74	36	45	237	23	96	40	126	32	52	38	52	59	52	54	10	58	16	54	7	.	23	67	343	21	93	32	93	42	-10	257	193	30	97	46	0	.	20	84	12	71	0	.	12775	3
	21-30 cm	109	45	8	100	40	61	143	38	318	27	580	21	1202	14	1519	12	525	21	1688	13	7	100	51	49	291	27	0	.	124	53	284	34	827	20	398	33	0	.	714	23	509	25	255	28	19	56	249	27	0	.	1213	13	310	27	396	28	676	19	121	60	344	21	116	41	124	30	420	23	310	31	108	58	627	25	300	29	345	30	499	23	339	36	677	20	247	37	174	33	297	27	59	51	267	29	429	23	404	24	340	29	233	32	0	.	97	67	0	.	133	35	0	.	307	27	346	31	117	40	494	24	391	27	351	27	348	31	70	53	30	54	159	36	102	44	290	27	260	37	0	.	587	29	46	73	89	41	479	23	194	35	270	33	78	46	120	56	106	59	59	48	61	71	5	.	18	100	770	20	251	27	133	41	41	65	409	28	285	29	0	.	39	71	38	88	0	.	26811	3
	31-40 cm	152	40	18	100	78	54	245	49	682	24	1011	20	1860	13	2382	11	724	22	2390	12	13	100	138	52	326	32	0	.	146	55	479	29	1073	20	591	25	0	.	894	21	462	28	453	23	31	71	315	36	0	.	2521	12	501	26	579	26	1030	20	168	37	560	26	287	38	255	30	618	21	530	28	108	34	544	24	549	28	456	29	782	20	443	28	1120	19	380	31	256	41	472	27	90	49	516	25	614	24	488	24	397	31	397	29	0	.	74	61	0	.	160	41	0	.	228	32	346	27	187	37	335	24	174	32	324	29	256	32	60	64	46	48	210	38	56	52	507	27	289	36	4	100	718	22	113	66	123	38	687	20	238	36	440	27	132	41	120	55	96	50	151	48	72	61	0	.	12	100	783	20	280	30	296	34	58	55	551	23	442	27	0	.	55	100	30	80	0	.	37778	3
	41-50 cm	288	34	48	84	70	68	284	33	750	23	1500	20	2350	14	3067	11	1047	21	2620	12	52	100	57	58	477	29	0	.	88	64	569	27	1068	20	775	27	0	.	1289	18	517	26	563	23	53	50	248	44	0	.	2765	12	483	25	692	27	1569	17	251	36	618	22	346	39	300	31	1053	19	279	33	74	46	619	24	588	26	572	30	891	22	488	29	1611	18	224	39	282	28	549	26	115	46	546	23	603	22	599	28	575	26	346	30	0	.	64	55	0	.	134	35	0	.	171	31	189	28	70	46	261	29	201	33	230	32	172	34	74	51	124	65	363	37	107	50	673	26	238	37	32	100	684	22	40	90	190	41	798	20	361	29	501	26	191	34	147	58	237	45	120	52	20	85	3	.	0	.	650	22	445	29	289	38	146	52	658	22	570	28	0	.	66	100	18	72	0	.	44058	2
	51-60 cm	241	40	13	100	36	74	222	40	565	28	1526	22	2501	14	3955	11	969	21	1899	14	12	100	137	70	439	32	0	.	41	58	422	34	980	20	552	28	0	.	868	21	360	39	534	25	46	61	198	44	0	.	1617	13	560	27	748	25	1349	20	250	34	646	27	252	44	257	30	765	20	254	42	117	44	805	29	653	29	191	35	955	23	775	27	1518	17	138	54	264	39	257	42	203	57	531	28	705	24	617	25	529	28	429	35	0	.	39	72	0	.	267	42	0	.	68	47	151	37	43	51	224	31	168	37	205	32	162	43	44	75	56	86	195	39	115	73	734	30	281	40	12	100	527	28	57	83	218	37	395	23	482	31	394	34	304	44	80	73	188	54	290	43	142	55	0	.	0	.	367	29	552	29	233	46	66	58	660	27	366	32	0	.	0	.	54	100	0	.	40040	3
	61-70 cm	182	46	0	.	0	.	98	45	239	39	927	27	1267	20	2311	14	635	27	728	27	0	.	80	60	262	41	0	.	16	100	287	36	520	33	309	38	0	.	383	26	240	34	340	29	27	71	73	59	0	.	825	20	620	34	541	30	663	25	110	47	229	30	75	71	155	52	885	21	111	46	79	74	348	35	212	34	201	38	466	33	289	35	1134	23	17	100	126	54	77	50	46	71	147	48	560	30	190	38	337	34	107	54	0	.	54	74	0	.	69	50	0	.	45	75	132	59	44	100	161	35	43	70	79	47	91	53	42	72	39	71	173	45	137	51	208	41	76	50	0	0	391	40	34	74	122	58	247	29	346	36	175	42	95	49	0	.	181	43	35	72	78	84	0	.	0	.	256	40	203	41	255	54	54	75	509	27	142	44	0	.	0	.	18	100	0	.	22012	4
	71-80 cm	0	.	0	.	0	.	141	86	122	60	260	38	540	35	1224	17	570	28	481	33	0	.	46	71	84	78	0	.	53	100	143	49	124	55	193	44	0	.	203	39	55	76	187	37	41	100	59	63	0	.	496	27	275	40	182	49	335	36	168	56	126	53	0	.	198	40	203	45	0	.	40	71	152	46	201	51	111	52	225	49	328	42	682	29	0	.	40	100	0	.	55	73	0	.	294	40	113	50	291	55	83	58	0	.	25	100	0	.	77	72	0	.	0	.	43	61	0	.	84	46	118	61	68	52	50	71	55	100	52	100	71	59	38	71	179	48	154	69	0	.	76	58	0	.	30	100	51	72	153	53	67	58	61	72	0	.	0	.	86	76	97	80	0	.	0	.	51	59	154	43	54	71	47	71	110	50	53	71	0	.	0	.	0	.	0	.	11226	6
	81-90 cm	0	.	0	.	0	.	68	71	0	.	51	100	232	39	553	27	206	45	107	58	0	.	0	.	0	.	0	.	0	.	43	100	58	71	40	100	0	.	113	52	24	100	41	74	0	.	42	74	0	.	181	39	0	.	0	.	58	72	31	100	35	100	0	.	0	.	110	76	0	.	42	100	0	.	71	73	54	100	0	.	67	71	351	55	0	.	0	.	29	100	0	.	0	.	83	71	31	100	126	52	34	100	0	.	0	.	0	.	39	100	0	.	14	100	16	100	0	.	68	83	31	100	24	100	0	.	0	.	25	100	41	100	57	100	34	100	90	59	0	.	44	100	0	.	0	.	38	100	0	.	0	.	39	100	0	.	33	100	44	100	0	.	0	.	0	.	68	61	0	.	119	60	0	.	131	50	0	.	0	.	0	.	0	.	0	.	3835	10
	91-100 cm	0	.	0	.	0	.	33	100	0	.	0	.	142	65	64	100	49	100	0	0	0	.	0	.	0	.	0	.	0	.	0	.	27	100	0	.	0	.	31	100	0	.	36	100	0	.	64	72	0	.	72	71	31	100	0	.	0	.	0	.	46	100	39	100	0	.	88	100	0	.	0	.	90	100	0	.	33	100	24	100	0	0	101	71	0	.	0	.	0	.	0	.	37	100	35	100	0	.	24	100	0	.	0	.	0	.	0	.	28	100	0	.	0	.	0	0	0	.	0	.	0	0	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	0	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	34	100	0	.	0	.	0	.	0	.	46	100	0	.	0	.	28	100	0	.	0	.	0	.	0	.	0	.	0	.	1200	20
	>100 cm	0	.	41	100	0	.	0	.	0	.	0	.	62	100	73	100	40	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	66	76	0	.	0	.	0	.	0	.	0	.	39	100	0	.	0	.	0	.	0	.	0	.	0	.	126	100	0	.	0	.	0	.	0	.	0	.	0	.	0	0	0	.	35	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	58	71	0	.	0	.	0	.	0	.	132	60	0	.	214	100	0	.	0	.	30	100	0	.	33	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	33	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	982	31
	total	999	32	128	71	227	60	1273	29	2794	22	6041	17	10891	11	15872	9	5077	16	10613	10	84	100	529	51	1981	25	0	.	494	47	2322	25	4986	15	3052	23	0	.	4798	16	2348	20	2552	19	236	53	1404	27	0	.	10469	10	2995	21	3345	20	6014	16	1143	29	2793	18	1152	32	1499	25	4387	17	1595	26	644	37	3438	20	2681	22	2074	24	4084	18	2894	21	7413	15	1080	28	1252	25	1811	21	604	39	2135	21	3674	18	2574	21	2831	21	1737	26	0	.	411	51	0	.	1116	31	0	.	1259	26	1403	22	536	31	1992	18	1399	24	1500	22	1194	28	431	43	401	51	1303	30	675	38	2847	22	1481	30	59	86	3263	20	319	68	807	32	2933	16	1871	24	1973	21	953	29	518	50	928	37	796	42	488	46	15	.	53	83	3369	17	1977	23	1472	31	431	52	3221	18	1956	24	0	.	179	82	171	72	0	.	200716	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	278	25	276	24	238	33	235	30	0	.	0	.	53	37	102	27	746	13	17	74	61	38	102	36	84	30	0	.	77	48	91	42	5	.	198	39	0	.	18	.	14	75	32	55	0	.	0	.	0	.	248	28	104	39	183	34	28	64	58	36	0	.	21	46	-1	.	0	.	3	100	17	75	54	67	120	34	83	58	31	70	58	45	0	.	221	24	80	33	27	44	140	44	67	31	31	80	0	.	2	100	121	29	247	28	250	40	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	17	72	0	.	27	71	64	47	68	51	37	60	56	44	56	48	2	218	78	35	56	47	0	.	60	49	33	57	95	29	36	61	11	43	0	.	46	50	0	.	0	.	148	33	30	57	57	43	119	30	55	64	97	34	117	41	74	37	131	35	0	.	6391	5
	21-30 cm	410	19	505	25	391	23	416	33	0	.	0	.	118	45	276	32	1492	13	54	66	108	34	212	30	159	35	1	.	120	31	243	36	0	.	304	36	0	.	0	.	26	75	22	53	0	.	0	.	0	.	403	21	196	30	239	28	78	62	43	47	0	.	52	50	12	.	0	.	4	100	88	80	41	66	221	35	57	74	23	74	113	61	0	.	562	23	117	45	83	41	131	36	243	37	28	73	0	.	5	100	291	34	344	31	456	27	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	99	83	26	100	53	61	168	43	70	50	71	71	97	48	95	49	29	71	96	37	131	51	0	.	139	49	76	43	215	34	100	46	59	49	0	.	99	45	0	.	0	.	203	35	67	54	141	67	194	29	73	71	158	30	307	31	183	31	300	28	0	.	11935	4
	31-40 cm	709	20	425	23	623	26	569	23	0	.	0	.	255	40	352	30	1767	12	32	81	176	44	256	29	388	33	13	.	251	36	281	38	33	.	402	31	0	.	0	.	21	60	40	64	0	.	0	.	0	.	732	22	344	30	499	34	90	64	47	45	0	.	91	55	6	.	0	.	21	100	37	77	85	72	249	41	131	49	57	73	184	43	0	.	683	19	280	27	207	36	312	29	362	30	81	76	0	.	90	87	410	36	404	25	486	26	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	75	74	11	100	61	67	131	42	54	72	25	60	71	61	108	51	27	77	129	34	160	46	0	.	98	45	188	41	435	31	124	38	72	53	0	.	188	39	0	.	0	.	109	35	56	58	150	42	306	32	77	55	390	32	386	28	339	35	263	33	0	.	16517	4
	41-50 cm	867	19	398	26	525	24	854	20	0	.	0	.	376	47	391	38	2351	11	72	64	252	33	431	30	307	30	22	.	288	44	280	44	61	.	297	31	0	.	0	.	67	73	41	56	0	.	0	.	0	.	930	19	521	31	522	27	64	53	129	43	0	.	135	46	15	.	0	.	41	71	67	100	10	100	228	39	83	61	74	46	165	44	0	.	1027	21	255	35	367	40	350	30	344	30	32	73	0	.	89	59	364	41	507	28	546	26	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	42	80	67	100	41	65	124	54	40	53	35	84	94	44	156	45	27	100	351	34	77	52	0	.	45	42	225	43	356	30	182	42	130	48	0	.	191	38	0	.	0	.	80	42	90	57	191	44	379	26	60	71	390	28	335	30	357	32	404	27	0	.	19215	4
	51-60 cm	507	24	560	25	504	25	896	24	0	.	0	.	290	43	429	32	2453	14	9	100	332	36	251	40	304	34	40	.	246	43	282	35	31	.	372	32	0	.	6	.	22	73	44	61	0	.	0	.	0	.	671	22	484	40	415	31	26	100	63	52	0	.	148	67	0	.	0	.	29	71	0	.	70	100	226	46	71	56	65	68	166	40	0	.	616	25	548	31	131	44	289	43	222	33	35	100	0	.	41	71	246	51	398	37	473	26	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	29	100	12	100	16	100	61	64	135	82	40	100	117	47	49	62	76	70	294	42	24	71	0	.	33	58	323	38	408	35	112	47	57	50	0	.	204	37	0	.	0	.	11	100	42	78	425	38	388	27	101	83	374	29	472	36	410	33	485	28	0	.	17709	4
	61-70 cm	390	29	376	36	238	36	703	24	0	.	0	.	107	73	247	39	1531	17	0	.	281	38	136	57	83	59	0	.	142	46	56	59	48	.	178	48	0	.	0	.	0	.	12	100	0	.	0	.	0	.	253	33	331	35	337	38	114	60	54	100	0	.	0	.	0	.	0	.	16	100	8	100	41	100	152	47	0	.	0	0	90	59	0	.	507	32	408	32	14	100	177	43	80	82	24	100	0	.	50	71	105	68	151	43	219	46	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	12	100	0	.	0	.	16	100	16	100	0	.	71	58	58	100	19	100	171	48	0	.	0	.	0	.	17	100	63	71	49	58	112	51	0	.	302	52	0	.	0	.	40	61	55	100	223	37	336	36	12	100	165	48	146	47	103	54	440	36	0	.	10086	6
	71-80 cm	245	38	215	41	142	54	328	35	0	.	0	.	0	.	111	60	545	29	0	.	62	71	50	71	93	62	25	.	27	100	60	71	21	.	127	63	0	.	0	.	18	100	0	.	0	.	0	.	0	.	70	50	60	71	28	100	40	100	21	100	0	.	50	71	0	.	0	.	0	.	0	.	0	.	57	72	49	75	27	100	140	60	0	.	119	45	259	37	0	.	0	.	74	78	0	.	0	.	84	100	17	100	159	53	80	73	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	16	100	0	.	20	100	24	100	21	100	0	.	30	100	0	.	0	.	189	51	0	.	0	.	0	.	29	100	24	100	0	.	117	56	0	.	20	100	0	.	0	.	10	100	0	.	32	100	168	41	18	100	46	100	84	58	76	58	137	45	0	.	4467	9
	81-90 cm	111	63	32	100	113	51	97	73	0	.	0	.	0	.	44	100	263	40	0	.	32	100	33	100	41	100	0	.	32	100	0	.	23	.	33	100	0	.	0	.	0	.	34	100	0	.	0	.	0	.	25	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	27	100	0	.	39	100	0	.	61	71	170	45	0	.	27	100	0	.	0	.	0	.	41	100	0	.	70	100	154	59	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	68	62	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	26	100	0	.	0	.	0	.	0	.	40	100	116	78	0	.	82	72	58	71	145	54	0	.	0	.	2039	14
	91-100 cm	26	100	0	.	0	.	0	.	0	.	0	.	0	.	46	100	116	75	0	.	0	.	45	100	0	.	0	.	44	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	95	100	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	.	0	.	0	.	34	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	50	100	0	.	0	.	0	.	0	.	0	.	0	.	496	34
	>100 cm	0	.	35	100	0	.	47	100	0	.	0	.	0	.	42	100	0	.	0	.	0	.	60	100	0	.	0	.	0	.	0	.	0	.	38	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	.	242	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	39	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	32	100	0	.	534	50
	total	3544	15	2823	18	2775	18	4146	17	0	.	0	.	1200	39	2038	24	11263	9	185	64	1303	27	1577	24	1460	25	101	.	1225	32	1293	30	222	.	1948	24	0	.	24	.	168	54	225	52	0	.	0	.	0	.	3332	17	2040	26	2222	22	440	51	415	38	0	.	497	46	32	.	0	.	114	73	218	71	301	69	1253	30	501	39	277	46	956	36	0	.	3796	16	2118	23	830	34	1427	24	1393	27	231	63	0	.	403	61	1555	31	2375	23	2907	20	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	289	71	116	100	219	58	589	38	403	51	208	64	536	38	521	42	179	59	1419	29	447	39	0	.	414	40	890	33	1597	27	602	36	593	42	0	.	1076	34	0	.	0	.	602	30	341	48	1258	30	2056	22	396	56	1702	24	1906	24	1687	25	2193	22	0	.	89390	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	.	45	49	0	.	0	.	0	.	21	.	163	41	8	85	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	8	.	8	81	143	35	34	46	227	33	161	26	532	19	197	28	165	30	231	27	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	4	75	0	.	0	.	18	.	0	.	0	.	0	.	104	39	64	34	31	40	0	.	0	.	0	.	0	.	0	.	1	100	0	.	0	.	0	.	2166	8
	21-30 cm	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	93	42	0	.	0	.	0	.	21	.	268	32	12	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	.	17	.	10	100	115	45	59	53	168	34	288	29	758	17	217	27	358	33	344	24	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	54	74	0	.	0	.	14	.	0	.	0	.	0	.	110	39	148	36	36	43	0	.	0	.	0	.	0	.	0	.	14	100	0	.	0	.	0	.	3105	7
	31-40 cm	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	141	45	0	.	0	.	11	.	0	.	202	31	13	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	.	9	.	6	100	56	41	78	60	209	42	284	30	736	18	173	32	195	29	344	33	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	22	82	0	.	0	.	7	.	0	.	0	.	0	.	103	39	100	40	9	123	0	.	0	.	0	.	0	.	0	.	66	73	0	.	0	.	0	.	2763	9
	41-50 cm	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	156	46	0	.	0	.	0	.	0	.	91	38	33	86	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	9	100	55	43	50	59	53	48	207	28	427	25	134	35	172	30	208	33	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	24	71	0	.	0	.	0	.	0	.	0	.	0	.	60	41	43	49	44	124	0	.	0	.	0	.	0	.	0	.	47	61	0	.	0	.	0	.	1815	10
	51-60 cm	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	65	71	0	.	0	.	9	.	0	.	102	50	19	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	.	13	.	0	.	11	71	6	100	75	45	122	36	153	41	143	32	91	66	169	38	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	118	53	41	100	24	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	1162	14
	61-70 cm	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	20	100	0	.	0	.	0	.	0	.	63	75	9	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	.	16	100	22	83	7	100	52	70	51	51	138	42	15	71	24	71	56	56	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	.	0	.	0	.	0	.	0	.	0	.	0	.	485	20
	71-80 cm	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	19	100	0	.	0	.	0	.	12	.	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	.	0	.	0	.	31	58	5	100	41	100	43	58	44	51	78	56	13	100	51	50	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	394	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	.	10	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	.	65	61	9	100	0	.	49	75	24	72	14	100	0	.	15	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	17	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	202	31
	91-100 cm	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	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	.	27	72	0	.	0	.	11	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	43	100	0	.	0	.	0	.	109	51
	>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	.	18	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	42	71	0	.	0	.	192	100	61	75	265	58	0	.	100	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	.	677	38
	total	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	539	39	0	.	0	.	19	.	54	.	974	29	93	73	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	47	.	50	96	569	28	248	46	825	27	1396	25	2901	14	1237	24	1019	25	1528	22	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	104	71	0	.	0	.	38	.	0	.	0	.	0	.	508	30	396	32	161	51	0	.	0	.	0	.	0	.	0	.	170	67	0	.	0	.	0	.	12878	6
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	305	23	276	24	242	32	274	27	124	37	185	26	1439	9	845	11	1059	11	720	13	61	38	122	31	186	20	0	.	106	37	237	22	365	20	395	26	45	49	320	22	465	15	377	15	862	16	1300	12	1117	11	987	13	335	21	390	22	431	15	103	33	188	24	58	30	83	28	246	35	167	28	208	23	370	22	226	23	222	31	342	19	240	23	195	21	294	21	190	24	155	29	176	36	158	21	415	21	210	26	167	28	229	21	247	28	317	34	206	28	407	18	219	21	470	20	341	18	607	17	673	14	473	18	478	18	154	28	113	41	197	23	199	24	199	26	324	22	149	30	66	42	242	24	106	32	91	34	240	22	160	30	159	28	160	22	105	39	64	45	10	58	63	39	983	10	795	13	1025	12	123	28	151	31	110	40	248	28	194	28	118	41	94	34	143	32	0	.	29431	2
	21-30 cm	519	18	514	25	430	21	559	26	331	27	580	21	2678	9	1830	11	2017	11	1742	13	115	33	263	26	450	21	1	.	248	30	699	23	969	18	715	24	93	42	854	20	1046	16	897	16	1252	13	2236	10	2039	10	1616	11	562	19	636	20	884	16	164	46	344	21	167	32	136	29	420	23	458	25	553	26	828	20	521	22	452	26	640	20	476	30	687	20	810	19	292	27	381	23	191	30	510	23	474	22	518	21	354	28	524	24	344	31	570	25	183	30	615	18	361	20	526	20	634	21	876	16	999	15	833	19	770	17	479	29	197	33	307	25	404	24	287	28	621	26	357	30	95	49	616	28	142	34	220	35	477	23	387	27	352	27	329	26	233	35	165	42	59	48	160	39	1810	11	1644	12	2146	11	318	24	274	40	235	26	481	26	443	22	321	30	222	28	338	27	0	.	57502	2
	31-40 cm	861	18	444	23	701	24	814	22	692	24	1011	20	4336	8	2916	10	2490	11	2428	12	189	42	395	26	715	23	13	.	426	29	974	20	1338	19	1033	19	141	45	980	21	1660	14	1285	15	1298	14	3263	9	2966	10	3253	10	906	19	1078	21	1295	17	214	31	560	26	378	32	261	30	618	21	652	24	505	22	861	19	798	23	661	23	1120	17	663	22	1130	18	1063	16	537	24	680	22	402	25	878	19	804	21	599	22	519	28	807	23	404	25	569	24	311	27	630	21	551	23	487	24	630	20	922	16	800	15	424	20	771	20	388	27	302	33	466	28	450	24	398	30	714	22	360	31	112	49	765	21	242	36	283	31	720	19	358	27	639	22	637	24	250	33	169	37	151	48	261	33	2264	11	1805	12	2321	11	336	27	446	26	364	29	627	21	832	21	452	26	393	33	293	31	0	.	78911	2
	41-50 cm	1155	16	446	25	594	22	1137	17	758	23	1500	20	5228	9	3640	10	3397	10	2692	11	304	32	488	27	784	21	22	.	494	33	1005	21	1342	18	1129	21	156	46	1552	16	2031	14	1376	14	1616	15	3679	10	3381	10	3695	10	1058	19	1214	19	1817	16	380	28	618	22	482	31	315	30	1053	19	374	26	437	27	876	19	817	22	746	25	1170	18	716	23	1721	17	1252	19	537	22	916	22	465	25	891	18	812	20	838	22	729	23	710	25	507	28	610	24	139	32	611	18	764	23	268	23	396	20	498	22	721	17	451	20	477	22	344	28	335	38	492	29	711	28	466	24	959	21	332	30	188	41	728	21	391	32	267	33	840	19	455	24	773	22	649	20	329	35	368	33	120	52	211	35	2204	11	1645	13	2149	12	535	26	480	29	525	24	718	21	960	20	382	27	422	31	423	26	0	.	89388	1
	51-60 cm	748	21	573	25	540	24	1118	21	565	28	1526	22	5126	10	4524	11	3422	11	1914	14	343	35	388	36	743	23	40	.	343	34	763	23	1276	18	1019	20	65	71	1088	18	1881	16	1343	16	1845	14	2929	11	2815	15	2288	11	1041	24	1163	20	1491	19	312	29	646	27	400	37	257	30	765	20	370	32	371	32	1073	23	878	24	297	28	1135	21	952	23	1631	17	753	22	812	24	388	31	492	35	753	22	841	22	805	21	604	26	675	29	398	37	525	24	258	29	787	20	419	26	180	28	273	26	196	34	676	17	316	29	429	22	311	32	148	38	260	33	520	28	513	32	1118	22	398	31	61	54	623	25	352	38	241	34	426	22	546	28	756	24	750	26	192	41	246	43	290	43	345	31	2359	12	1470	15	1780	13	594	27	658	29	454	24	761	26	740	21	472	36	410	33	539	27	0	.	80919	2
	61-70 cm	573	24	376	36	238	36	802	21	239	39	927	27	2549	13	2673	13	2165	14	728	27	281	38	217	42	346	34	0	.	178	39	343	32	658	28	542	28	20	100	550	23	935	19	667	21	954	18	1770	12	1287	20	1077	17	951	25	878	23	805	23	165	46	229	30	75	71	155	52	885	21	154	37	260	35	454	29	365	28	231	34	613	26	386	30	1253	22	524	31	534	28	92	45	224	37	228	42	706	25	239	34	399	30	213	43	151	43	272	40	190	43	328	25	344	30	108	47	183	44	182	40	290	25	96	42	251	40	126	43	130	41	149	45	334	31	309	32	460	34	154	37	58	100	450	36	205	42	122	58	247	29	382	33	225	35	188	36	49	58	293	33	35	72	381	45	1312	17	688	18	974	19	258	39	477	33	390	33	522	27	308	33	146	47	103	54	459	35	0	.	44435	3
	71-80 cm	245	38	215	41	142	54	469	35	122	60	260	38	1297	19	1366	16	1115	20	481	33	62	71	96	50	177	49	25	.	80	74	202	40	180	44	379	34	19	100	489	29	664	27	489	26	668	22	1127	19	465	22	567	24	334	35	210	45	397	32	189	51	126	53	50	71	198	40	203	45	15	100	156	43	219	39	258	43	174	40	282	41	517	32	727	28	119	45	299	35	0	.	55	73	74	78	366	36	144	45	375	48	100	51	159	53	106	61	227	33	252	36	168	37	57	78	86	42	44	51	235	29	173	44	148	35	115	42	175	68	256	51	154	40	293	33	297	36	184	60	0	.	101	50	189	51	30	100	51	72	153	53	96	50	101	52	0	.	117	56	86	76	117	69	1270	20	268	34	624	30	154	43	86	58	215	36	129	46	99	60	84	58	76	58	137	45	0	.	24303	4
	81-90 cm	111	63	32	100	113	51	165	52	0	.	51	100	502	28	628	25	469	30	165	51	32	100	33	100	41	100	0	.	32	100	43	100	104	50	73	71	0	.	162	40	193	49	292	33	282	32	533	24	267	32	206	36	0	.	0	.	58	72	31	100	35	100	0	.	0	.	110	76	34	100	42	100	49	100	71	73	81	75	69	58	106	58	351	55	61	71	170	45	29	100	27	100	0	.	83	71	31	100	167	46	34	100	70	100	154	59	37	100	239	36	152	44	48	77	65	62	24	72	99	61	31	100	61	59	0	.	49	100	25	100	113	54	175	47	105	51	90	59	0	.	44	100	68	62	0	.	38	100	0	.	0	.	39	100	0	.	33	100	44	100	26	100	417	28	195	36	207	36	0	.	159	51	116	78	131	50	82	72	58	71	145	54	0	.	0	.	9509	6
	91-100 cm	26	100	0	.	0	.	33	100	0	.	0	.	218	47	110	72	165	61	36	100	0	.	45	100	0	.	0	.	44	100	0	.	54	71	0	.	0	.	133	45	50	100	56	73	76	71	148	48	199	44	72	71	31	100	0	.	0	.	0	.	46	100	39	100	0	.	88	100	0	.	0	.	119	79	0	.	33	100	24	100	0	0	101	71	0	.	0	.	0	.	0	.	37	100	35	100	0	.	24	100	0	.	95	100	0	.	20	100	80	58	38	100	0	.	0	0	27	72	87	71	0	0	11	100	0	.	25	100	37	100	0	.	69	100	0	.	0	0	0	.	0	.	41	100	0	.	0	.	0	.	0	.	0	.	0	.	68	71	0	.	0	.	166	43	108	51	46	100	0	.	0	.	78	73	0	.	0	.	43	100	0	.	0	.	0	.	3078	12
	>100 cm	0	.	75	71	0	.	47	100	0	.	0	.	137	62	115	73	40	100	0	.	0	.	60	100	0	.	0	.	0	.	0	.	0	.	38	100	0	.	158	54	40	100	290	78	115	58	273	42	69	58	39	100	0	.	0	.	0	.	0	.	0	.	0	.	126	100	0	.	0	.	0	.	43	100	0	.	0	.	22	100	0	.	35	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	58	71	0	.	0	.	242	100	116	79	231	44	0	.	214	100	192	100	61	75	336	48	0	.	164	45	0	.	0	.	43	100	0	.	21	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	39	100	0	.	0	.	0	.	0	.	0	.	0	.	46	71	0	.	62	71	0	.	0	.	0	.	0	.	0	.	0	.	0	.	32	100	0	.	3579	16
	total	4543	14	2952	17	3002	17	5418	14	2832	22	6041	17	23510	7	18647	8	16340	8	10906	10	1387	26	2107	22	3441	18	101	.	1951	25	4265	17	6285	14	5324	16	539	39	6288	14	8964	11	7070	12	8969	10	17257	7	14606	8	13802	8	5216	16	5567	15	7180	14	1558	23	2793	18	1648	26	1531	25	4387	17	2223	21	2530	20	4890	16	3934	18	2897	19	5416	15	4057	18	7831	14	4876	14	3370	17	2641	18	2031	20	3528	16	4536	16	3385	18	3395	19	3292	20	2375	23	3364	18	1687	20	4181	14	3016	17	2359	17	2799	17	3437	12	4916	11	2797	16	3560	15	1916	23	1474	27	2233	22	2885	20	2729	19	4599	17	2024	24	580	38	3569	19	1738	27	1254	25	3039	16	2480	20	3000	17	2855	18	1159	29	1520	28	796	42	1563	27	12832	8	8618	10	11333	9	2317	21	2730	21	2487	20	3617	17	3657	17	2077	23	1866	24	2363	21	0	.	421054	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. 2281822. Birmensdorf, Swiss Federal Research Institute WSL

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