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mortality #16
Stemwood volume of all trees and shrubs with a diameter at breast height (dbh) ≥12 cm with bark that died naturally between two inventories (e.g. due to windthrow or insects) or disappeared (e.g. due to avalanches), but that were not harvested. Mortality is the sum of natural losses and the remaining mortality.

tree species (5 classes) #1157
Type of trees and shrubs ≥12 cm in diameter at breast height (dbh). The three most common species or species groups in Switzerland (spruce - Picea spp.; fir - Abies spp.; beech - Fagus sylvatica) are in individual classes, while the remaining species are classified as «other conifers» or «other broadleaves». Reference: Field Survey (MID 50: Baumart)

higher/lower altitude zone #2635
Areas in higher and lower altitude zones classified according to the system used for altitudinal vegetation belts in the guidelines for monitoring the sustainability and performance of protection forests (NaiS; Frehner et al. 2005). The boundary between the higher and lower altitudes runs between the «upper montane» and «lower montane» levels on the Northern Alps and between the «high montane» and «upper/lower montane» levels to the Southern Alps. The information is based on the altitudinal vegetation belts determined by experts (accessible forest sample plots of NFI4 on the 1.4-km network; Arge Frehner et al. 2020), as well as on the altitudinal vegetation belts modelled for the period 1981-2010 (other sample plots; Zischg et al. 2021).

canton #827
Regional demarcation with the cantons as a unit, with the two half-cantons, Basel-Land and Basel-Stadt, combined into one canton for statistical reasons.

accessible forest without shrub forest NFI1-NFI5 #2382
Forest that was less than two-thirds covered with shrubs in the five inventories NFI1 (1983-1985), NFI2 (1993-1995), NFI3 (2004-2006), NFI4 (2009-2017) and NFI5 (2018-2026) and was accessible on foot.

1.4 km grid, subgrids 1-5 #1746
Sub-grids 1, 2, 3, 4 and 5 of the field surveys on the sampling grid with a mesh size of 1.4 km (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.

NFI3–NFI4
mortality
tree species (5 classes) · higher/lower altitude zone
regional demarcation: canton
unit: 1000 m³/yr
evaluation area: accessible forest without shrub forest NFI1-NFI5
grid: 1.4 km grid, subgrids 1-5
change 2004/06–2009/17
		canton
		AG		AI		AR		BE		BL/BS		FR		GE		GL		GR		JU		LU		NE		NW		OW		SG		SH		SO		SZ		TG		TI		UR		VD		VS		ZG		ZH		Switzerland
tree species (5 classes)	higher/lower altitude zone	1000 m³/yr	±%	1000 m³/yr	±%	1000 m³/yr	±%	1000 m³/yr	±%	1000 m³/yr	±%	1000 m³/yr	±%	1000 m³/yr	±%	1000 m³/yr	±%	1000 m³/yr	±%	1000 m³/yr	±%	1000 m³/yr	±%	1000 m³/yr	±%	1000 m³/yr	±%	1000 m³/yr	±%	1000 m³/yr	±%	1000 m³/yr	±%	1000 m³/yr	±%	1000 m³/yr	±%	1000 m³/yr	±%	1000 m³/yr	±%	1000 m³/yr	±%	1000 m³/yr	±%	1000 m³/yr	±%	1000 m³/yr	±%	1000 m³/yr	±%	1000 m³/yr	±%
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	.
	lower altitude zone	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0
	higher altitude zone	0	.	0	0	0	0	0	0	0	0	0	0	0	.	0	0	0	0	0	0	0	0	0	0	0	0	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
spruce	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	.
	lower altitude zone	10	69	2	100	0	0	22	32	3	90	4	71	0	.	4	74	1	72	4	74	26	34	1	71	0	0	0	0	6	72	2	80	5	50	2	100	9	74	0	100	2	100	31	37	9	81	0	0	14	50	161	14
	higher altitude zone	0	.	0	72	3	89	61	30	0	.	13	43	0	.	6	72	120	24	2	100	84	43	2	156	4	59	8	54	10	77	0	.	0	100	15	60	0	.	14	62	13	51	25	71	58	33	0	100	0	0	444	14
	total	10	69	2	73	3	89	80	23	3	90	17	37	0	.	10	53	122	23	6	60	106	33	3	110	4	59	8	54	16	55	2	80	5	48	17	55	9	74	14	61	15	46	57	37	67	31	0	100	14	50	597	11
fir	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	.
	lower altitude zone	0	100	0	0	7	94	49	45	0	0	0	0	0	.	0	0	0	0	19	60	13	70	1	58	0	0	0	0	11	75	0	0	1	100	0	0	0	0	1	63	0	0	1	82	0	0	0	0	10	76	116	26
	higher altitude zone	0	.	0	0	1	100	22	40	0	.	9	67	0	.	0	0	3	100	1	100	3	92	3	79	0	0	0	0	9	62	0	.	0	0	0	1403	0	.	14	100	2	92	1	77	8	71	8	100	2	100	83	25
	total	0	100	0	0	7	85	72	34	0	0	9	67	0	.	0	0	3	100	20	57	16	60	4	57	0	0	0	0	20	49	0	0	1	100	0	1403	0	0	15	94	2	92	1	58	9	71	8	100	12	67	200	18
other conifers	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	.
	lower altitude zone	5	72	0	.	0	0	1	73	4	77	8	59	0	0	0	0	6	97	13	69	0	0	2	86	0	.	0	0	4	100	0	0	4	70	0	0	0	0	0	0	0	0	7	54	13	52	0	0	6	59	72	22
	higher altitude zone	0	.	0	.	0	0	0	0	0	.	0	.	0	.	0	0	48	28	0	0	0	0	0	.	0	.	0	0	0	0	0	.	0	0	0	0	0	.	3	92	4	100	0	0	58	34	0	.	0	.	106	21
	total	5	72	0	.	0	0	1	73	4	77	8	59	0	0	0	0	54	27	13	69	0	0	2	86	0	.	0	0	4	100	0	0	4	70	0	0	0	0	3	92	4	100	8	54	71	30	0	0	6	59	177	15
beech	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	.
	lower altitude zone	19	65	0	0	0	0	17	37	16	70	11	51	0	.	0	100	8	82	6	62	5	60	1	81	0	100	6	64	17	50	4	86	15	42	0	0	1	100	21	54	0	100	20	56	1	83	0	0	7	77	175	16
	higher altitude zone	0	.	0	100	0	0	3	84	0	0	0	0	0	.	0	100	0	0	0	100	2	100	1	100	0	0	0	0	6	87	0	.	0	0	1	100	0	.	0	0	0	0	5	68	0	0	4	100	0	0	24	36
	total	19	65	0	100	0	0	20	34	16	70	11	51	0	.	1	71	8	82	6	59	7	51	2	63	0	100	6	64	23	44	4	86	15	42	1	100	1	100	21	54	0	100	26	47	1	83	4	100	7	77	203	15
other broadleaves	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	.
	lower altitude zone	5	48	0	.	0	0	23	39	5	68	1	100	0	0	3	100	15	56	14	40	6	64	1	63	1	100	0	100	13	68	1	100	14	55	4	70	1	63	116	17	0	0	15	33	13	50	0	100	13	45	247	11
	higher altitude zone	0	.	0	100	0	0	5	46	0	0	9	44	0	.	3	68	16	36	1	100	1	75	1	78	0	0	3	74	4	72	0	.	0	0	5	64	0	.	3	46	4	77	3	62	14	37	0	.	0	0	72	16
	total	5	48	0	100	0	0	29	34	5	68	9	41	0	0	6	61	30	32	15	38	7	58	2	50	2	100	3	69	17	55	1	100	14	55	9	47	1	63	120	17	4	77	18	30	27	31	0	100	13	45	324	9
indeterminable	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	.
	lower altitude zone	0	0	0	.	0	0	0	0	0	0	0	0	0	.	0	0	0	0	0	0	0	0	0	.	0	.	0	.	0	0	0	.	0	0	0	0	0	0	0	0	0	.	0	0	0	0	0	.	0	0	0	0
	higher altitude zone	0	.	0	.	0	0	0	0	0	.	0	0	0	.	0	.	0	0	0	.	0	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
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	.
	lower altitude zone	40	39	2	100	7	94	112	24	28	46	24	34	0	0	7	59	31	40	56	32	50	28	7	40	2	80	6	62	50	32	6	57	39	29	6	60	10	65	138	16	2	93	74	24	36	36	0	100	50	27	771	7
	higher altitude zone	0	.	1	60	4	75	91	22	0	0	31	35	0	.	9	51	187	17	4	56	90	42	6	66	4	59	10	44	29	42	0	.	0	100	22	49	0	.	34	51	23	36	34	62	139	23	12	98	2	100	730	10
	total	40	39	2	61	11	64	203	17	28	46	55	24	0	0	16	38	217	16	60	30	136	28	13	38	6	47	17	36	79	25	6	57	39	29	27	41	10	65	173	16	25	34	110	25	174	20	13	96	51	26	1500	6

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. 1391195. Birmensdorf, Swiss Federal Research Institute WSL

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