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volume of bolewood (HG 2010) #211
Wood volume of the stem without bark or stump ≥7 cm in diameter (limit for merchantable wood) of all trees and shrubs with a diameter at breast height (dbh) ≥12 cm, based on the stem-form functions according to Kaufmann (2001). The definition of the assortments is based on the 2010 edition of the Swiss trading customs for raw timber (HG 2010).

type of assortment #2221
Sorting of roundwood into five length classes (4 for conifers, 1 for broadleaves) on the basis of the 2010 and 2021 editions of the Swiss Trading Customs for Raw Timber (HG 2010, Waldwirtschaft Schweiz et al. 2010). Reference: Forest Service Survey (MID 2020: Längensortierung des Nadelrundholzes)

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)

production region #49
Demarcation of Switzerland into five regions (Jura, Plateau, Pre-Alps, Alps and Southern Alps) with relatively uniform growth and timber production conditions. The production regions were established by the Federal Office of Forestry long before the first National Forest Inventory (NFI1, 1983-1985). With a small exception along Lake Geneva, the boundaries of the production regions still follow the municipal boundaries of the time. Unlike the NFI, the Forestry Statistics of the Federal Statistical Office don't use the production regions as demarcation but rather the forestry zones, whose boundaries are somewhat different.

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.

NFI5
volume of bolewood (HG 2010)
type of assortment · tree species (5 classes)
regional demarcation: production region
unit: 1000 m³
evaluation area: accessible forest without shrub forest NFI1-NFI5
grid: 1.4 km grid, subgrids 1-5
state 2018/26
		production region
		Jura		Plateau		Pre-Alps		Alps		Southern Alps		Switzerland
type of assortment	tree species (5 classes)	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%
n/a	n/a	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	0	0	0	0	0	0	0	0	0	0	0	0
	fir	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
	beech	0	0	0	0	0	0	0	0	0	0	0	0
	other broadleaves	0	0	0	0	0	0	0	0	0	0	0	0
	indeterminable	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
coniferous wood	n/a	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	0	.	49	74	388	65	622	46	0	.	1059	36
	fir	0	.	46	100	190	72	0	.	0	.	236	61
	other conifers	0	.	19	100	0	.	158	55	0	.	177	50
	beech	0	.	0	.	0	.	0	.	0	.	0	.
	other broadleaves	0	.	0	.	0	.	0	.	0	.	0	.
	indeterminable	0	.	0	.	0	.	0	.	0	.	0	.
	total	0	.	114	75	578	51	781	41	0	.	1473	30
coniferous shortwood	n/a	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	5433	12	14937	7	34101	5	54364	4	9979	14	118813	3
	fir	3382	16	9480	10	15212	7	6255	13	1709	25	36037	5
	other conifers	1450	24	3311	15	694	32	16728	6	3989	12	26172	5
	beech	0	.	0	.	0	.	0	.	0	.	0	.
	other broadleaves	0	.	0	.	0	.	0	.	0	.	0	.
	indeterminable	0	.	0	0	0	0	0	0	0	0	0	0
	total	10265	9	27727	6	50006	4	77347	3	15676	10	181022	2
coniferous mediumwood	n/a	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	913	29	1255	29	2995	21	2908	20	212	61	8283	12
	fir	580	28	1030	28	2423	21	1142	28	23	100	5199	13
	other conifers	266	36	201	39	76	71	874	27	285	51	1702	18
	beech	0	.	0	.	0	.	0	.	0	.	0	.
	other broadleaves	0	.	0	.	0	.	0	.	0	.	0	.
	indeterminable	0	.	0	.	0	0	0	0	0	.	0	0
	total	1759	22	2487	21	5494	18	4925	17	519	43	15183	10
coniferous longwood	n/a	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	10479	9	4915	17	2347	25	1036	41	0	.	18778	8
	fir	10215	9	2708	18	1265	30	399	78	0	.	14587	8
	other conifers	696	32	839	33	215	98	28	60	0	.	1779	23
	beech	0	.	0	.	0	.	0	.	0	.	0	.
	other broadleaves	0	.	0	.	0	.	0	.	0	.	0	.
	indeterminable	0	0	0	.	0	0	0	.	0	.	0	0
	total	21391	7	8462	13	3828	22	1463	43	0	.	35143	6
broadleaf roundwood	n/a	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	0	.	0	.	0	.	0	.	0	.	0	.
	fir	0	.	0	.	0	.	0	.	0	.	0	.
	other conifers	0	.	0	.	0	.	0	.	0	.	0	.
	beech	18431	5	19261	5	14381	7	7281	10	5110	11	64463	3
	other broadleaves	8109	8	13523	7	6713	9	7227	9	10310	7	45881	3
	indeterminable	19	61	6	87	5	47	35	56	4	58	70	34
	total	26559	4	32790	4	21098	6	14543	7	15424	6	110414	2
total	n/a	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	16826	6	21155	6	39831	5	58931	4	10190	13	146933	2
	fir	14177	7	13264	8	19090	6	7796	11	1732	24	56058	4
	other conifers	2412	17	4371	13	985	32	17789	6	4273	12	29830	5
	beech	18431	5	19261	5	14381	7	7281	10	5110	11	64463	3
	other broadleaves	8109	8	13523	7	6713	9	7227	9	10310	7	45881	3
	indeterminable	19	61	6	87	5	47	35	56	4	58	70	34
	total	59974	3	71580	3	81004	3	99058	2	31619	5	343236	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. 1403848. Birmensdorf, Swiss Federal Research Institute WSL

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