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total basal area NFI1 #238
Sum of the stem cross-sectional areas at a height of 1.3 m (level for measuring diameter at breast height [dbh]) of all living and dead trees and shrubs (standing and lying) with a dbh ≥12 cm according to the method used in NFI1. In NFI1, dead trees were only included if their wood was still usable. The total basal area NFI1 corresponds to the sum of the basal area and the deadwood basal area NFI1.

forest formations (NaiS; 10 classes) #2637
Combination of the 18 groups of NaiS site types, each with a similar objective for the main tree species (NAISGGROB20), into 10 large associations known as «forest formations». *As the characterisation of the site types in the NaiS-NFI project is on a small scale, it is possible that non-forest site types such as meadow, pasture and rock may be present in sample plots that are classified as «forest» in NFI. Similarly, «forest without shrub forest“ may also contain «shrub forest» site types.

main tree species #90
Type of trees and shrubs ≥12 cm in diameter at breast height (dbh) with the ten most common species or species groups in Switzerland ('main tree species') categorised, and the classes 'other conifers' and 'other broadleaves' for the remaining species. The main tree species are: spruce (Picea spp.), fir (Abies spp.), pine (Pinus sylvestris, P. nigra, P. strobus, P. mugo subsp. uncinata), larch (Larix spp.), Arolla pine (Pinus cembra), beech (Fagus sylvatica), maple (Acer spp.), ash (Fraxinus spp.), oak (Quercus spp.) and chestnut (Castanea sativa). Reference: Field Survey (MID 50: Baumart)

biogeographical region #2586
Demarcation of Switzerland into six regions with similar flora and fauna. The six regions correspond to the basic categories in the publication «The Biogeographical Regions of Switzerland», which was published by FOEN in 2022.

protection forest (2022): a.f.w.s.f. #2652
Accessible forest without shrub forest («a.f.w.s.f.»), i.e. forest that is less than two-thirds covered with shrubs and can be accessed on foot, which is situated in a forest that the cantons designated «protection forest» in 2022 according to the harmonised criteria of SilvaProtect-CH (Losey & Wehrli 2013).

1.4-km grid #410
NFI's sampling grid with a mesh size of 1.4 km. The 1.4-km grid is the grid size covering all the previous terrestrial Inventories, which is why it is also called the base grid.

Estimates and standard error of the estimates

The results published in the NFI tables are estimates for variables in the Swiss forest (population parameters) whose true values are not known and must therefore be extrapolated (estimated) from the NFI sample data.

The extrapolations carry uncertainties. However, the accuracy of the extrapolations can be reliably estimated from the NFI sample, which is designed to be a random sample. To this end, all NFI tables include a second figure in addition to the estimate itself, namely the standard error of the estimate.

In most tables the percent standard error is reported (±%), but the absolute standard error (±) is also reported occasionally, especially for estimated percentages. The relationship between absolute and percent standard error is as follows:

percent standard error = absolute standard error / estimate × 100

absolute standard error = percent standard error × estimate / 100

Information on the forest road network is based on a full survey of all forest roads. In this case, there is no need to specify a standard error because there is no uncertainty caused by sampling.

Confidence interval of the estimate

With the estimate and the standard error of the estimate, the limits of the so-called confidence interval of the estimate can be calculated as:

lower limit = estimate – tQ × absolute standard error

upper limit = estimate + tQ × absolute standard error

If the simple standard error is used for the calculation (tQ = 1), then the 68% confidence interval is formed. In this case, the true value of the population parameter has a 68% probability of lying within this confidence interval of the estimate. If the double standard error is used (tQ = 2), then there is a 95% probability that the true value lies within this 95% confidence interval.

Significance of the estimate

The confidence interval can be used to statistically test whether the estimated population parameter is larger or smaller than a specific reference or target value, or whether two estimated population parameters truly differ (in the real population). For practical applications, proceed as follows: if a reference value lies outside the confidence interval, the estimated population value can be interpreted as being significantly different from it; if it lies within the confidence interval, the difference between the estimated population parameter and the reference value can be interpreted as random or not significant. When two population parameters are compared, they can be interpreted as differing significantly if their confidence intervals do not overlap.

Dealing with missing values

When calculating a results table, data are not always available for all combinations of characteristics^* of the classification variables and regional demarcation applied. In most cases, this indicates that the attribute estimated with the respective target variable does not occur or occurs only very rarely. Usually, the value 0 is used (imputed). However, as this value is not based on direct measurements, the associated standard error is represented with a full stop [.]. If the imputed value of 0 is referred to in the calculation, e.g. in the case of percentages or certain change estimates, no value can be entered. In this case, the estimated value and standard error are both represented with a full stop [.].

For example, no Arolla pines have been found and measured in the Swiss Plateau to date (growing stock of Arolla pines by production region). The values can be assumed to be missing because Arolla pine does not occur in the Swiss Plateau and therefore the growing stock there must be 0.

^* e.g. ‘Arolla pine’ characteristic of the classification variable ‘tree species’ and ‘Swiss plateau’ characteristic of the ‘regional demarcation’

Changes

There are two types of changes in the NFI:

The first type involves specific target variables relating to components of change, such as increment, fellings, mortality and losses. These target variables are only available for two consecutive inventory cycles, e.g. NFI3–NFI4. In the evaluation of components of change, the classification variable characteristic of the second inventory cycle is assigned to the first inventory cycle. These evaluations therefore do not take into account potential changes in a classification variable characteristic from the earlier to the later inventory (e.g. from private to public ownership).

With the second type of change, the difference in target variables, such as number of stems, growing stock or forest area, is used to assess the change between two inventory cycles. Target variables are generally used to represent states, such as that in NFI4, but can also indicate the net change between any two inventory cycles, e.g. NFI1–NFI4. In evaluations of change using these target variables, the change in a classification variable characteristic is considered in the analysis. Consequently, one can detect, for example, that the forest area without shrub forest increased between the two inventory cycles. This only has an effect on classification variables whose characteristic (class) can actually change, e.g. the affiliation with a forest area or the tree condition.

NFI1
total basal area NFI1
forest formations (NaiS; 10 classes) · main tree species
regional demarcation: biogeographical region
unit: m²/ha
evaluation area: protection forest (2022): a.f.w.s.f.
grid: 1.4-km grid
state 1983/85
		biogeographical region
		Jura		Plateau		Northern Alps		Western Central-Alps		Eastern Central-Alps		Southern Alps		Switzerland
forest formations (NaiS; 10 classes)	main tree species	m²/ha	±%	m²/ha	±%	m²/ha	±%	m²/ha	±%	m²/ha	±%	m²/ha	±%	m²/ha	±%
n/a	n/a	0.0	.	0.0	.	0.0	.	0.0	.	0.0	.	0.0	.	0.0	.
	spruce	17.4	0	0.4	88	19.5	23	9.3	84	9.7	67	5.0	71	12.9	21
	fir	0.0	.	0.4	90	2.7	39	0.0	.	0.0	.	0.9	93	1.5	37
	pine	0.0	.	0.3	88	1.0	98	0.4	89	1.7	92	0.0	.	0.8	69
	larch	0.0	.	0.0	.	0.0	.	4.2	41	6.5	58	1.0	94	1.4	44
	Arolla pine	0.0	.	0.0	.	0.0	.	0.4	89	0.0	.	0.0	.	0.0	99
	other conifers	0.0	.	0.0	.	0.0	.	0.0	.	0.0	.	0.0	.	0.0	.
	beech	0.0	.	8.1	55	6.6	30	0.0	.	0.0	.	3.0	78	4.5	27
	maple	0.0	.	12.8	40	1.8	40	0.0	.	0.0	.	2.1	71	2.5	33
	ash	0.0	.	1.9	32	1.0	48	0.3	90	0.0	.	0.0	.	0.7	36
	oak	0.0	.	1.4	90	0.6	98	0.0	.	0.0	.	8.1	94	1.7	76
	sweet chestnut	0.0	.	0.0	.	0.1	97	0.0	.	0.0	.	9.5	62	1.6	67
	other broadleaves	0.0	.	9.9	64	1.8	35	5.4	90	2.4	58	3.2	41	3.3	30
	indeterminable	0.0	.	0.0	.	0.0	.	0.0	.	0.0	.	0.0	.	0.0	.
	total	17.4	0	35.4	13	35.0	12	19.9	37	20.4	29	32.7	19	30.9	9
beech forests	n/a	0.0	.	0.0	.	0.0	.	0.0	.	0.0	.	0.0	.	0.0	.
	spruce	5.0	15	9.0	14	11.2	9	1.7	62	3.7	53	0.9	42	7.4	7
	fir	6.5	13	7.1	13	6.0	12	0.3	95	2.7	47	0.1	74	5.2	7
	pine	1.9	30	1.0	29	0.7	33	6.3	33	4.9	59	0.0	.	1.1	16
	larch	0.0	.	0.1	86	0.3	41	2.3	71	3.0	52	1.9	32	0.6	22
	Arolla pine	0.0	.	0.0	.	0.0	.	0.0	.	0.0	.	0.0	.	0.0	.
	other conifers	0.1	95	0.2	50	0.1	49	0.0	.	0.0	.	0.0	.	0.1	36
	beech	13.5	8	9.3	11	13.4	8	7.5	17	11.5	37	14.3	8	12.5	4
	maple	1.5	16	1.8	20	1.5	12	0.4	64	1.3	42	0.1	63	1.3	9
	ash	1.1	24	3.2	15	1.5	16	2.0	54	1.3	50	0.0	68	1.5	10
	oak	0.3	48	0.8	28	0.3	34	0.2	72	0.8	96	0.2	58	0.4	19
	sweet chestnut	0.0	.	0.0	.	0.0	100	0.0	.	0.0	.	2.2	24	0.4	25
	other broadleaves	1.0	17	1.0	28	1.4	15	0.7	67	2.3	31	3.2	18	1.5	9
	indeterminable	0.0	.	0.0	.	0.0	.	0.0	.	0.0	.	0.0	.	0.0	.
	total	31.0	4	33.4	4	36.5	3	21.6	11	31.4	16	22.8	5	32.0	2
silver fir-beech forests	n/a	0.0	.	0.0	.	0.0	.	0.0	.	0.0	.	0.0	.	0.0	.
	spruce	9.7	16	21.5	22	19.6	6	9.0	9	13.5	14	4.1	35	16.9	5
	fir	8.0	20	7.9	27	7.8	8	11.6	54	5.1	26	8.6	21	7.7	7
	pine	1.1	73	0.0	.	0.1	64	1.4	55	1.4	78	0.0	.	0.3	42
	larch	0.4	99	0.0	.	0.3	76	4.2	42	2.4	43	3.6	36	0.8	28
	Arolla pine	0.0	.	0.0	.	0.0	.	0.0	.	0.0	.	0.0	.	0.0	.
	other conifers	0.0	.	0.1	96	0.0	.	0.0	.	0.0	.	0.0	.	0.0	100
	beech	8.3	18	5.5	34	6.0	9	10.9	31	8.5	24	10.5	16	6.8	7
	maple	1.1	24	0.2	96	1.5	13	0.0	.	1.5	51	0.0	98	1.3	12
	ash	0.7	57	0.5	68	0.4	23	0.0	.	0.0	.	0.0	.	0.4	21
	oak	0.0	.	0.0	.	0.0	.	0.0	.	0.0	.	0.0	69	0.0	71
	sweet chestnut	0.0	.	0.0	.	0.0	.	0.0	.	0.0	.	0.1	99	0.0	100
	other broadleaves	0.6	67	0.1	97	0.8	17	0.2	89	0.5	44	1.0	32	0.7	14
	indeterminable	0.0	.	0.0	.	0.0	.	0.0	.	0.0	.	0.0	.	0.0	.
	total	29.8	6	35.8	13	36.4	3	37.3	7	32.8	9	27.9	9	34.8	3
other boradleaved forests	n/a	0.0	.	0.0	.	0.0	.	0.0	.	0.0	.	0.0	.	0.0	.
	spruce	6.4	63	11.6	21	12.6	13	5.3	38	4.4	49	0.4	55	4.6	12
	fir	2.3	59	4.3	36	3.0	26	0.3	98	0.3	95	0.0	.	1.1	21
	pine	0.0	.	0.0	.	0.0	.	4.4	33	0.0	.	0.0	.	0.4	37
	larch	0.0	.	0.6	97	0.0	.	2.3	53	0.0	.	0.1	61	0.3	40
	Arolla pine	0.0	.	0.0	.	0.0	.	0.0	.	0.0	.	0.0	.	0.0	.
	other conifers	0.0	.	0.1	97	0.0	.	0.0	.	0.0	.	0.0	.	0.0	100
	beech	2.0	47	2.6	28	1.0	35	0.1	98	0.4	95	0.6	28	0.8	17
	maple	4.6	51	2.4	34	2.8	20	0.6	74	3.0	85	0.2	45	1.2	17
	ash	5.4	86	3.6	31	2.5	23	0.5	44	0.1	95	0.8	23	1.4	16
	oak	0.0	.	0.0	97	0.3	71	1.5	38	0.5	95	1.8	19	1.2	17
	sweet chestnut	0.0	.	0.0	.	0.0	.	1.0	57	0.0	.	12.1	11	6.9	11
	other broadleaves	1.4	64	0.7	50	2.4	26	2.3	36	3.2	53	4.1	12	3.2	10
	indeterminable	0.0	.	0.0	.	0.0	.	0.0	.	0.0	.	0.0	.	0.0	.
	total	22.0	34	25.9	13	24.5	8	18.2	14	11.9	31	20.2	6	21.1	4
silver fir-spruce forests	n/a	0.0	.	0.0	.	0.0	.	0.0	.	0.0	.	0.0	.	0.0	.
	spruce	0.0	.	0.0	.	32.5	5	15.4	13	30.7	7	15.2	12	25.9	4
	fir	0.0	.	0.0	.	3.8	17	5.7	27	1.9	25	2.9	33	3.4	12
	pine	0.0	.	0.0	.	0.3	72	1.8	56	1.0	39	0.7	52	0.7	27
	larch	0.0	.	0.0	.	0.0	100	7.4	25	1.1	34	7.3	15	2.9	13
	Arolla pine	0.0	.	0.0	.	0.0	100	0.0	.	0.0	.	0.0	.	0.0	100
	other conifers	0.0	.	0.0	.	0.0	.	0.0	.	0.0	.	0.0	.	0.0	.
	beech	0.0	.	0.0	.	0.3	43	0.0	.	0.0	99	0.7	42	0.3	30
	maple	0.0	.	0.0	.	0.8	28	0.0	99	0.1	93	0.0	.	0.3	27
	ash	0.0	.	0.0	.	0.0	.	0.0	.	0.0	.	0.0	.	0.0	.
	oak	0.0	.	0.0	.	0.0	.	0.0	.	0.1	99	0.0	.	0.0	100
	sweet chestnut	0.0	.	0.0	.	0.0	.	0.0	.	0.0	.	0.0	.	0.0	.
	other broadleaves	0.0	.	0.0	.	0.5	27	0.8	54	0.3	44	0.8	34	0.5	19
	indeterminable	0.0	.	0.0	.	0.0	.	0.0	.	0.0	.	0.0	.	0.0	.
	total	0.0	.	0.0	.	38.2	4	31.2	9	35.2	6	27.5	7	34.1	3
spruce forests	n/a	0.0	.	0.0	.	0.0	.	0.0	.	0.0	.	0.0	.	0.0	.
	spruce	0.0	.	0.0	.	28.5	7	22.0	6	28.2	5	21.6	9	25.1	3
	fir	0.0	.	0.0	.	1.5	46	0.3	59	0.1	57	0.2	63	0.4	32
	pine	0.0	.	0.0	.	0.2	59	2.0	30	1.0	28	0.5	100	1.1	21
	larch	0.0	.	0.0	.	0.2	60	10.1	9	4.0	14	7.3	15	6.0	7
	Arolla pine	0.0	.	0.0	.	0.2	99	0.6	35	0.5	39	0.1	99	0.4	25
	other conifers	0.0	.	0.0	.	0.0	99	0.0	.	0.0	100	0.0	.	0.0	71
	beech	0.0	.	0.0	.	0.0	100	0.0	.	0.0	.	0.0	100	0.0	86
	maple	0.0	.	0.0	.	0.0	58	0.0	.	0.1	100	0.1	74	0.0	54
	ash	0.0	.	0.0	.	0.0	.	0.0	.	0.0	.	0.0	.	0.0	.
	oak	0.0	.	0.0	.	0.0	.	0.0	.	0.0	.	0.0	.	0.0	.
	sweet chestnut	0.0	.	0.0	.	0.0	.	0.0	.	0.0	.	0.0	99	0.0	100
	other broadleaves	0.0	.	0.0	.	0.1	46	0.3	30	0.0	51	0.3	43	0.2	22
	indeterminable	0.0	.	0.0	.	0.0	.	0.0	.	0.0	.	0.0	.	0.0	.
	total	0.0	.	0.0	.	30.8	6	35.4	4	33.9	4	30.1	6	33.3	2
Arolla pine and larch forests	n/a	0.0	.	0.0	.	0.0	.	0.0	.	0.0	.	0.0	.	0.0	.
	spruce	0.0	.	0.0	.	0.0	.	2.4	35	1.5	40	0.0	.	1.7	27
	fir	0.0	.	0.0	.	0.0	.	0.0	.	0.0	.	0.0	.	0.0	.
	pine	0.0	.	0.0	.	0.0	.	0.0	99	0.2	69	0.0	.	0.1	64
	larch	0.0	.	0.0	.	0.0	.	12.7	15	13.0	17	18.9	18	13.5	10
	Arolla pine	0.0	.	0.0	.	0.0	.	8.5	18	10.5	16	0.0	.	8.6	13
	other conifers	0.0	.	0.0	.	0.0	.	0.0	.	0.4	99	0.0	.	0.2	99
	beech	0.0	.	0.0	.	0.0	.	0.0	.	0.0	.	0.0	.	0.0	.
	maple	0.0	.	0.0	.	0.0	.	0.0	.	0.0	.	0.0	.	0.0	.
	ash	0.0	.	0.0	.	0.0	.	0.0	.	0.0	.	0.0	.	0.0	.
	oak	0.0	.	0.0	.	0.0	.	0.0	.	0.0	.	0.0	.	0.0	.
	sweet chestnut	0.0	.	0.0	.	0.0	.	0.0	.	0.0	.	0.0	.	0.0	.
	other broadleaves	0.0	.	0.0	.	0.0	.	0.0	99	0.0	.	0.0	.	0.0	99
	indeterminable	0.0	.	0.0	.	0.0	.	0.0	.	0.0	.	0.0	.	0.0	.
	total	0.0	.	0.0	.	0.0	.	23.5	10	25.6	8	18.9	18	24.0	6
pine forests	n/a	0.0	.	0.0	.	0.0	.	0.0	.	0.0	.	0.0	.	0.0	.
	spruce	0.0	.	3.3	0	16.7	45	2.6	39	6.1	73	0.0	.	5.7	32
	fir	0.0	.	0.0	.	2.0	93	0.0	.	0.0	.	0.0	.	0.3	99
	pine	0.0	.	14.3	0	10.0	44	19.1	13	18.8	28	8.9	0	17.0	12
	larch	0.0	.	0.0	.	0.0	.	0.5	57	3.0	64	9.3	0	1.1	43
	Arolla pine	0.0	.	0.0	.	0.0	.	0.0	.	0.1	92	0.0	.	0.0	99
	other conifers	0.0	.	0.0	.	0.1	93	0.0	.	0.0	.	4.0	0	0.1	81
	beech	0.0	.	3.3	0	0.3	92	0.0	98	0.0	.	0.0	.	0.1	64
	maple	0.0	.	3.3	0	0.0	.	0.1	98	0.0	.	0.0	.	0.1	73
	ash	0.0	.	0.6	0	0.0	.	0.0	98	0.0	.	0.0	.	0.0	71
	oak	0.0	.	0.0	.	0.0	.	0.0	.	0.0	.	0.0	.	0.0	.
	sweet chestnut	0.0	.	0.0	.	0.0	.	0.0	.	0.0	.	0.0	.	0.0	.
	other broadleaves	0.0	.	3.9	0	0.1	92	0.3	52	0.0	.	0.0	.	0.3	45
	indeterminable	0.0	.	0.0	.	0.0	.	0.0	.	0.0	.	0.0	.	0.0	.
	total	0.0	.	28.8	0	29.2	27	22.7	10	28.1	21	22.2	0	24.9	9
pioneer forests	n/a	0.0	.	0.0	.	0.0	.	0.0	.	0.0	.	0.0	.	0.0	.
	spruce	0.0	.	0.0	.	7.6	60	0.1	96	3.8	54	1.3	58	2.2	36
	fir	0.0	.	0.0	.	1.5	58	0.0	.	0.0	.	0.4	99	0.4	64
	pine	0.0	.	0.0	.	0.0	.	1.3	67	1.8	96	0.0	.	0.5	62
	larch	0.0	.	0.0	.	0.0	.	1.0	82	0.0	.	1.8	55	1.2	49
	Arolla pine	0.0	.	0.0	.	0.0	.	0.0	.	0.0	.	0.0	.	0.0	.
	other conifers	0.0	.	0.0	.	0.0	.	0.0	.	0.0	.	0.0	.	0.0	.
	beech	0.0	.	0.0	.	0.0	.	0.0	.	0.0	.	0.7	43	0.4	44
	maple	0.0	.	0.0	.	0.9	95	0.4	96	0.5	95	0.2	87	0.3	48
	ash	0.0	.	0.0	.	0.2	95	0.0	96	3.3	57	0.2	51	0.6	49
	oak	0.0	.	0.0	.	0.0	.	0.1	96	0.0	.	0.1	99	0.1	79
	sweet chestnut	0.0	.	0.0	.	0.0	.	0.0	.	0.0	.	0.6	57	0.3	57
	other broadleaves	0.0	.	0.0	.	6.6	39	5.0	33	5.4	38	7.7	19	6.7	14
	indeterminable	0.0	.	0.0	.	0.0	.	0.0	.	0.0	.	0.0	.	0.0	.
	total	0.0	.	0.0	.	16.7	29	7.9	30	14.9	27	13.0	13	12.8	10
shrub forests*	n/a	0.0	.	0.0	.	0.0	.	0.0	.	0.0	.	0.0	.	0.0	.
	spruce	0.0	.	11.6	0	1.1	90	0.2	80	0.0	.	4.0	92	2.3	60
	fir	0.0	.	0.0	.	0.0	.	0.0	.	0.0	.	0.0	.	0.0	.
	pine	0.0	.	0.0	.	0.0	.	0.0	.	0.0	.	0.0	.	0.0	.
	larch	0.0	.	0.0	.	0.0	.	4.1	81	0.5	81	1.5	92	1.3	63
	Arolla pine	0.0	.	0.0	.	0.0	.	0.2	81	4.1	82	0.0	.	0.7	92
	other conifers	0.0	.	0.0	.	0.1	89	0.0	.	0.0	.	0.0	.	0.0	96
	beech	0.0	.	0.0	.	0.0	.	0.0	.	0.0	.	0.2	91	0.1	97
	maple	0.0	.	3.9	0	0.0	.	0.0	.	0.0	.	0.0	.	0.2	97
	ash	0.0	.	5.8	0	0.0	.	0.0	.	0.0	.	0.0	.	0.3	97
	oak	0.0	.	0.0	.	0.0	.	0.0	.	0.0	.	0.0	.	0.0	.
	sweet chestnut	0.0	.	0.0	.	0.0	.	0.0	.	0.0	.	0.0	.	0.0	.
	other broadleaves	0.0	.	0.7	0	0.2	89	7.2	83	0.0	.	0.3	58	1.4	85
	indeterminable	0.0	.	0.0	.	0.0	.	0.0	.	0.0	.	0.0	.	0.0	.
	total	0.0	.	22.0	0	1.4	69	11.8	44	4.7	69	6.0	61	6.4	32
non-forest*	n/a	0.0	.	0.0	.	0.0	.	0.0	.	0.0	.	0.0	.	0.0	.
	spruce	3.9	89	8.4	29	12.3	23	1.2	60	22.1	48	0.2	96	8.4	21
	fir	3.6	83	3.8	59	2.5	33	0.0	.	0.0	.	0.0	.	1.6	30
	pine	0.0	.	0.0	.	0.6	72	0.0	.	2.0	90	0.0	.	0.5	58
	larch	0.0	.	0.0	.	0.0	.	7.9	58	0.0	.	1.1	54	1.2	55
	Arolla pine	0.0	.	0.0	.	0.0	.	0.0	.	0.0	.	0.0	.	0.0	.
	other conifers	0.0	.	0.0	.	0.0	.	0.0	.	0.0	.	0.0	.	0.0	.
	beech	6.7	64	0.0	.	2.0	45	0.0	.	0.0	.	7.3	57	2.9	36
	maple	0.0	.	0.7	83	0.4	47	0.3	94	0.0	.	0.0	.	0.3	40
	ash	1.4	41	0.0	.	0.8	56	0.0	.	0.0	.	1.1	70	0.7	39
	oak	0.0	.	0.0	.	0.1	98	0.0	.	0.0	.	0.5	96	0.1	75
	sweet chestnut	0.0	.	0.0	.	0.3	97	0.0	.	0.0	.	15.8	61	3.3	62
	other broadleaves	0.8	89	0.0	.	0.9	40	0.4	94	0.0	.	1.0	38	0.7	27
	indeterminable	0.0	.	0.0	.	0.0	.	0.0	.	0.0	.	0.0	.	0.0	.
	total	16.4	42	12.8	24	19.8	13	9.7	47	24.1	43	27.0	35	19.7	13
total	n/a	0.0	.	0.0	.	0.0	.	0.0	.	0.0	.	0.0	.	0.0	.
	spruce	6.1	11	9.9	11	19.5	3	14.0	6	21.6	5	6.4	9	14.6	2
	fir	6.5	11	6.5	11	5.2	6	1.1	24	1.0	18	1.0	20	3.3	5
	pine	1.6	28	0.8	28	0.4	23	3.2	15	1.5	19	0.2	49	1.0	9
	larch	0.1	100	0.1	65	0.2	40	7.8	7	3.8	11	3.3	10	2.5	5
	Arolla pine	0.0	.	0.0	.	0.0	90	1.1	20	1.3	19	0.0	100	0.4	14
	other conifers	0.1	95	0.1	46	0.0	42	0.0	.	0.0	88	0.0	100	0.0	30
	beech	11.6	7	8.0	10	5.7	6	0.4	29	1.2	24	3.9	9	4.5	4
	maple	1.5	14	2.0	17	1.3	8	0.1	45	0.3	33	0.1	30	0.8	6
	ash	1.2	24	2.9	13	0.8	11	0.1	39	0.1	46	0.3	21	0.7	8
	oak	0.2	48	0.7	27	0.1	30	0.1	39	0.1	61	0.7	22	0.3	14
	sweet chestnut	0.0	.	0.0	.	0.0	64	0.1	60	0.0	.	4.6	11	1.0	11
	other broadleaves	0.9	17	1.1	26	1.0	9	0.9	19	0.5	22	2.8	9	1.3	6
	indeterminable	0.0	.	0.0	.	0.0	.	0.0	.	0.0	.	0.0	.	0.0	.
	total	29.9	3	32.3	4	34.3	2	28.9	3	31.4	3	23.4	3	30.3	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. 1396856. Birmensdorf, Swiss Federal Research Institute WSL

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