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number of stems of young forest plants #406
Number of living conifers and conifers ≥10 cm in height and ≤11.9 cm in diameter at breast height (dbh).

size classe (young forest; 5 classes) #2623
Size of young forest plants ≥10 cm in height and ≤11.9 cm in diameter at breast height (dbh) – in five size classes (two height and three dbh classes). Reference: Field Survey (MID 507: Jungwaldklasse)

main tree species in young forest (counting) #2625
Species of young forest plants ≥10 cm in height and ≤11.9 cm in diameter at breast height (dbh) with individual classes for the ten most important species or species groups in Switzerland («main tree species»), as well as the classes «other conifers», «other broadleaves» and «species not assessed in all inventories». 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 1051: Jungwaldpflanzenart - Zählung)

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.

stockable and accessible forest without shrub forest #1876
Stockable part of the accessible forest without shrub forest, i.e. accessible forest without shrub forest excluding the area of forest roads, recreational facilities, streams, avalanche paths, etc.

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
number of stems of young forest plants
size classe (young forest; 5 classes) · main tree species in young forest (counting)
regional demarcation: production region
unit: n/ha
evaluation area: stockable and 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
size classe (young forest; 5 classes)	main tree species in young forest (counting)	n/ha	±%	n/ha	±%	n/ha	±%	n/ha	±%	n/ha	±%	n/ha	±%
n/a	n/a	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	0	.	0	.	0	.	0	.	0	.	0	.
	fir	0	.	0	.	0	.	0	.	0	.	0	.
	pine	0	.	0	.	0	.	0	.	0	.	0	.
	larch	0	.	0	.	0	.	0	.	0	.	0	.
	Arolla pine	0	.	0	.	0	.	0	.	0	.	0	.
	other conifers	0	.	0	.	0	.	0	.	0	.	0	.
	beech	0	.	0	.	0	.	0	.	0	.	0	.
	maple	0	.	0	.	0	.	0	.	0	.	0	.
	ash	0	.	0	.	0	.	0	.	0	.	0	.
	oak	0	.	0	.	0	.	0	.	0	.	0	.
	sweet chestnut	0	.	0	.	0	.	0	.	0	.	0	.
	other broadleaves	0	.	0	.	0	.	0	.	0	.	0	.
	species not assessed in all inventories	0	.	0	.	0	.	0	.	0	.	0	.
	total	0	.	0	.	0	.	0	.	0	.	0	.
height 10-39 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	546	29	848	26	1007	18	609	14	38	71	641	10
	fir	971	16	1792	13	1274	21	117	28	53	46	772	9
	pine	8	100	7	100	0	.	24	38	0	.	11	33
	larch	0	.	0	.	0	.	129	90	17	71	45	85
	Arolla pine	0	.	0	.	0	.	28	73	16	100	12	62
	other conifers	43	71	43	51	7	100	0	.	0	.	16	40
	beech	5470	16	3958	17	2264	29	1106	34	902	36	2533	10
	maple	7054	17	7624	17	3200	19	546	21	292	27	3379	10
	ash	4419	16	4125	15	2192	19	1733	34	3002	28	2869	10
	oak	1313	36	796	26	54	39	111	29	317	56	451	20
	sweet chestnut	0	.	0	.	0	.	6	70	96	40	15	36
	other broadleaves	1105	20	887	28	901	16	1547	18	418	25	1085	10
	species not assessed in all inventories	0	.	0	.	0	.	0	.	0	.	0	.
	total	20928	11	20079	9	10898	12	5956	14	5151	19	11828	5
height 40-129 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	206	30	607	31	551	16	540	14	36	35	434	11
	fir	235	27	719	18	229	25	33	32	16	60	228	12
	pine	3	100	8	61	2	100	41	50	3	100	17	42
	larch	0	.	2	100	0	.	68	49	6	70	24	47
	Arolla pine	0	.	0	.	0	.	21	32	6	100	8	30
	other conifers	0	.	6	58	0	.	0	.	0	.	1	58
	beech	3624	14	2380	13	1093	20	323	21	183	60	1366	8
	maple	853	28	1712	19	529	27	94	18	41	33	593	13
	ash	323	19	887	15	399	23	151	21	373	45	391	10
	oak	5	71	88	65	3	100	21	34	22	59	28	40
	sweet chestnut	0	.	0	.	0	.	0	.	23	42	3	43
	other broadleaves	456	17	503	15	435	22	397	14	221	31	410	8
	species not assessed in all inventories	0	.	0	.	0	.	0	.	0	.	0	.
	total	5705	11	6914	9	3241	11	1689	9	930	23	3503	5
DBH 0-3.9 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	83	23	120	16	223	12	214	12	34	34	153	7
	fir	110	38	251	21	77	25	17	25	19	31	87	14
	pine	2	71	2	71	0	.	24	27	5	81	9	25
	larch	1	100	4	60	0	.	33	23	16	48	14	20
	Arolla pine	0	.	0	.	0	.	9	25	0	.	3	25
	other conifers	1	100	6	50	0	.	0	.	1	100	1	42
	beech	2015	11	1495	13	732	17	200	38	75	39	818	8
	maple	257	17	565	17	228	19	42	21	10	48	205	10
	ash	52	21	103	22	121	44	35	24	17	34	64	18
	oak	1	100	31	45	1	100	6	65	1	100	8	35
	sweet chestnut	0	.	1	100	0	.	0	100	22	29	3	27
	other broadleaves	196	19	245	17	259	13	170	11	88	20	194	7
	species not assessed in all inventories	0	.	0	.	0	.	0	.	0	.	0	.
	total	2717	9	2822	9	1640	10	750	11	289	14	1559	5
DBH 4-7.9 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	37	19	52	14	103	11	103	10	36	23	74	6
	fir	43	17	47	17	37	18	8	25	8	45	26	9
	pine	0	100	1	70	1	100	14	29	5	71	6	26
	larch	0	100	2	73	0	.	13	18	13	27	6	15
	Arolla pine	0	.	0	.	0	.	7	27	0	100	2	26
	other conifers	0	.	2	47	0	.	0	.	0	.	0	47
	beech	116	12	96	13	50	15	17	19	28	35	55	7
	maple	37	16	34	17	17	18	11	19	4	37	19	9
	ash	9	29	18	26	12	39	5	27	4	40	9	15
	oak	0	100	2	37	0	.	1	61	2	62	1	28
	sweet chestnut	0	.	0	.	0	.	0	.	4	36	1	36
	other broadleaves	31	16	39	13	41	15	46	14	60	17	43	7
	species not assessed in all inventories	0	.	0	.	0	.	0	.	0	.	0	.
	total	275	7	292	7	261	7	224	7	165	11	244	3
DBH 8-11.9 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	15	19	33	15	43	12	56	9	24	26	39	6
	fir	27	17	17	20	22	19	5	23	5	44	14	10
	pine	0	100	1	62	0	.	9	22	5	73	4	21
	larch	1	71	1	61	1	79	9	18	13	32	5	15
	Arolla pine	0	.	0	.	0	.	5	27	0	.	2	27
	other conifers	0	100	0	100	0	.	0	.	0	.	0	71
	beech	46	13	39	13	21	17	6	25	23	23	24	7
	maple	17	19	12	20	8	32	7	24	3	47	9	11
	ash	5	48	4	35	4	60	4	37	3	41	4	20
	oak	6	70	3	47	0	100	2	46	1	71	2	33
	sweet chestnut	0	.	0	.	0	.	0	.	2	45	0	45
	other broadleaves	13	21	20	15	17	20	19	16	36	16	20	8
	species not assessed in all inventories	0	.	0	.	0	.	0	.	0	.	0	.
	total	131	8	131	7	117	7	121	6	114	10	123	3
total	n/a	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	888	21	1659	22	1927	12	1522	10	167	25	1340	7
	fir	1386	14	2826	11	1639	17	180	22	100	30	1127	8
	pine	13	91	19	46	3	81	112	27	18	66	46	23
	larch	2	61	10	66	1	79	251	59	65	27	95	52
	Arolla pine	0	.	0	.	0	.	70	33	23	77	26	31
	other conifers	44	69	57	39	7	100	0	.	1	100	19	34
	beech	11271	11	7968	12	4161	19	1652	25	1211	32	4796	7
	maple	8217	16	9946	14	3982	17	699	17	350	23	4205	9
	ash	4808	15	5137	14	2727	17	1928	31	3399	29	3337	9
	oak	1325	36	921	25	58	37	141	28	343	53	491	19
	sweet chestnut	0	.	1	100	0	.	7	66	148	28	22	25
	other broadleaves	1801	15	1693	17	1654	13	2180	13	822	19	1752	7
	species not assessed in all inventories	0	.	0	.	0	.	0	.	0	.	0	.
	total	29756	9	30238	7	16158	9	8739	10	6648	17	17256	4

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. 1196589. Birmensdorf, Swiss Federal Research Institute WSL

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