Selection from the list of topics

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: economic region
unit: n/ha
evaluation area: stockable and accessible forest without shrub forest NFI2-NFI5
grid: 1.4 km grid, subgrids 1-5
state 2018/26
		economic region
		Western Jura		Eastern Jura		Western Plateau		Central Plateau		Eastern Plateau		Western Pre-Alps		Central Pre-Alps		Eastern Pre-Alps		Northwestern Alps		Central Alps		Northeastern Alps		Southwestern Alps		Southeastern 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/ha	±%	n/ha	±%	n/ha	±%	n/ha	±%	n/ha	±%	n/ha	±%	n/ha	±%	n/ha	±%	n/ha	±%
n/a	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	0	.	0	.	0	.	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	.	0	.	0	.	0	.
	pine	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	larch	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	Arolla pine	0	.	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	.	0	.
	beech	0	.	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	.	0	.
	ash	0	.	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	.	0	.
	sweet chestnut	0	.	0	.	0	.	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	.	0	.	0	.	0	.
	species not assessed in all inventories	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	.
height 10-39 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	651	32	271	58	383	54	1357	42	723	34	316	39	1183	23	1136	34	1326	27	437	41	255	59	585	25	578	27	47	71	681	11
	fir	1110	18	584	41	1097	35	1967	18	1921	20	1357	33	675	22	2240	34	438	41	114	70	140	72	90	85	10	100	46	50	839	9
	pine	10	100	0	.	38	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	14	100	43	50	0	.	9	38
	larch	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	32	74	10	100	5	62
	Arolla pine	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	72	100	0	.	21	100	9	78
	other conifers	57	71	0	.	0	.	56	57	52	79	0	.	0	.	21	100	0	.	0	.	0	.	0	.	0	.	0	.	18	40
	beech	5263	20	7146	23	6165	47	2394	25	4435	20	678	51	1292	52	4996	38	4204	59	856	47	3791	58	224	53	412	39	1066	38	2825	10
	maple	5461	19	13573	32	6519	33	3478	31	11454	22	2664	52	1278	36	6048	26	1765	39	842	40	985	47	233	38	337	41	336	29	3721	10
	ash	4050	20	6271	23	3425	28	3225	45	5236	16	1539	52	1222	32	4340	26	1261	35	2024	45	2759	35	4000	58	750	45	3522	30	3163	10
	oak	1179	47	2006	54	2102	36	150	55	783	42	0	.	33	71	128	46	0	.	0	.	0	.	461	29	0	.	390	58	506	20
	sweet chestnut	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	23	100	0	.	0	.	0	.	10	100	111	43	15	38
	other broadleaves	1280	22	614	33	1360	56	409	33	1098	40	1396	35	914	24	619	24	2138	24	1385	30	945	48	2311	43	1147	18	396	29	1121	11
	species not assessed in all inventories	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	total	19060	13	30464	20	21090	19	13037	20	25702	12	7949	26	6598	17	19526	18	11154	28	5658	24	8875	30	7991	32	3319	16	5945	21	12912	5
height 40-129 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	261	32	49	49	480	63	757	62	588	35	532	34	778	22	325	26	768	27	375	35	161	43	366	31	668	25	37	40	445	12
	fir	288	28	87	50	85	42	944	26	806	26	147	33	367	34	124	29	149	45	22	99	37	70	31	53	4	100	12	74	250	13
	pine	4	100	0	.	35	74	7	100	0	.	0	.	0	.	0	.	9	100	0	.	0	.	66	86	67	70	0	.	17	46
	larch	0	.	0	.	0	.	0	.	5	100	0	.	0	.	0	.	0	.	0	.	0	.	10	71	96	37	4	100	13	33
	Arolla pine	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	21	50	35	43	7	100	7	32
	other conifers	0	.	0	.	0	.	6	100	9	71	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	1	58
	beech	2971	14	6608	28	3895	30	1871	27	2239	16	887	44	861	39	1676	29	952	36	623	69	571	28	46	58	209	44	227	61	1510	8
	maple	564	29	2003	49	1674	50	627	30	2577	23	874	64	238	34	644	38	336	25	200	51	53	74	52	49	16	71	48	35	644	13
	ash	279	23	492	34	726	36	553	29	1224	20	466	47	420	41	364	36	237	39	433	56	288	49	125	36	117	53	464	46	430	10
	oak	7	71	0	.	366	86	29	49	23	52	0	.	6	100	0	.	0	.	0	.	0	.	73	39	12	58	16	71	30	43
	sweet chestnut	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	21	44	2	44
	other broadleaves	442	20	531	31	668	26	246	34	649	21	697	64	486	23	252	23	785	32	480	35	154	40	339	26	340	32	222	38	425	9
	species not assessed in all inventories	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	total	4815	10	9770	26	7930	20	5040	18	8121	12	3602	28	3157	15	3383	19	3237	17	2133	30	1263	21	1129	16	1563	17	1059	25	3775	5
DBH 0-3.9 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	96	25	22	66	161	43	118	28	112	20	302	34	257	15	161	23	323	22	103	42	149	52	159	25	283	23	36	38	159	8
	fir	93	22	190	97	42	58	440	28	213	33	53	37	93	41	87	36	20	47	24	56	19	74	32	44	1	100	17	39	96	15
	pine	1	100	0	.	4	100	2	100	0	.	0	.	0	.	0	.	0	.	23	99	0	.	26	48	41	42	7	81	9	28
	larch	0	.	4	100	13	73	0	.	4	100	0	.	0	.	0	.	0	.	0	.	0	.	25	59	50	31	3	70	10	25
	Arolla pine	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	9	52	16	35	0	.	3	29
	other conifers	1	100	0	.	5	100	3	100	8	66	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	1	100	2	42
	beech	1718	14	3307	20	1190	49	919	22	2102	15	570	46	770	30	938	22	183	33	1371	88	274	28	23	62	183	47	91	40	909	8
	maple	239	22	304	24	136	38	399	38	875	20	208	29	173	27	332	34	104	28	170	62	19	57	33	46	14	67	11	55	223	11
	ash	41	26	84	39	67	43	66	40	142	30	40	49	211	58	40	59	46	65	59	62	89	53	28	44	31	50	19	36	67	19
	oak	1	100	0	.	115	65	17	37	10	53	0	.	2	100	0	.	0	.	0	.	0	.	22	69	1	100	0	.	9	36
	sweet chestnut	0	.	0	.	5	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	2	100	0	.	23	32	3	29
	other broadleaves	205	21	170	42	313	42	158	35	276	23	437	24	253	22	171	30	248	24	249	31	127	35	152	26	83	32	86	23	190	8
	species not assessed in all inventories	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	total	2396	11	4081	17	2052	30	2122	15	3743	11	1609	21	1759	16	1729	16	923	14	2000	61	677	25	511	15	703	17	294	16	1679	5
DBH 4-7.9 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	44	21	17	50	45	37	61	24	50	21	166	25	104	14	81	23	149	20	99	26	103	43	76	18	126	21	36	22	77	7
	fir	50	15	28	82	31	38	87	20	27	38	27	30	43	24	39	37	6	53	21	45	2	100	16	43	1	71	10	45	29	9
	pine	1	100	0	.	0	.	0	.	2	70	0	.	2	100	0	.	0	.	0	.	0	.	16	39	25	46	3	100	5	30
	larch	0	.	0	.	2	100	0	.	4	84	0	.	0	.	0	.	1	100	0	.	0	.	13	32	12	31	8	40	4	19
	Arolla pine	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	7	39	9	47	1	100	2	32
	other conifers	0	.	0	.	4	100	1	100	2	57	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	47
	beech	98	15	177	23	33	31	91	21	129	18	21	37	59	20	66	24	28	28	38	51	67	38	2	58	9	40	34	36	60	7
	maple	35	19	47	30	15	45	15	31	54	21	20	37	13	39	16	31	32	36	16	65	7	74	8	34	4	42	4	43	20	9
	ash	6	43	14	50	11	46	18	55	21	31	9	99	11	59	5	50	10	38	0	.	12	52	6	66	1	71	5	40	9	15
	oak	0	.	0	.	4	70	1	100	3	50	0	.	0	.	0	.	0	.	0	.	0	.	3	61	0	.	2	74	1	30
	sweet chestnut	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	5	36	1	36
	other broadleaves	29	20	44	28	39	29	38	25	38	19	85	29	28	23	33	31	59	22	79	37	18	50	54	35	18	51	58	20	40	8
	species not assessed in all inventories	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	total	262	8	327	17	182	14	312	11	328	10	328	15	259	10	240	14	285	14	252	22	210	26	201	14	205	15	166	13	248	4
DBH 8-11.9 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	14	21	21	41	24	38	54	23	24	23	65	26	45	17	35	23	66	21	62	33	64	33	35	18	78	15	21	25	40	6
	fir	34	18	9	66	17	46	26	29	10	39	6	58	32	23	24	38	5	61	18	39	8	57	9	42	1	71	5	50	15	10
	pine	0	.	0	.	0	.	1	100	2	100	0	.	0	.	0	.	0	.	10	99	0	.	10	39	10	40	4	100	3	26
	larch	0	100	0	.	2	100	1	100	2	100	4	99	0	.	1	100	0	.	0	.	0	.	13	27	7	36	6	50	3	19
	Arolla pine	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	1	100	8	37	0	.	1	35
	other conifers	0	100	0	.	0	.	1	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	71
	beech	38	16	78	21	28	33	40	23	44	17	8	49	27	22	18	29	10	49	18	46	33	50	0	.	2	74	27	24	25	7
	maple	15	23	27	32	18	48	6	40	14	25	2	100	6	41	6	51	13	46	3	99	12	52	6	35	4	87	3	52	9	11
	ash	3	45	5	74	3	100	6	56	3	53	13	88	1	100	1	100	12	70	3	99	2	99	4	52	1	100	3	45	4	22
	oak	7	79	2	99	2	100	1	100	6	56	0	.	0	.	0	.	0	.	0	.	0	.	6	50	0	.	1	100	2	37
	sweet chestnut	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	3	45	0	45
	other broadleaves	13	24	12	62	20	38	17	27	22	20	25	39	18	32	12	39	10	43	18	46	17	41	26	21	12	54	34	20	19	9
	species not assessed in all inventories	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	total	123	10	153	15	114	19	153	13	126	10	122	18	130	10	97	15	117	16	133	23	136	20	110	11	123	12	105	11	122	4
total	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	1066	22	380	43	1094	48	2347	37	1497	28	1380	25	2366	17	1738	25	2633	19	1077	26	731	30	1221	19	1733	18	178	28	1402	8
	fir	1575	15	897	39	1272	31	3464	16	2977	17	1589	28	1211	19	2513	31	618	36	199	43	205	51	179	46	17	61	90	34	1229	8
	pine	16	100	0	.	78	59	10	70	3	79	0	.	2	100	0	.	9	100	33	76	0	.	132	60	186	38	13	89	44	27
	larch	0	100	4	100	17	66	1	100	14	95	4	99	0	.	1	100	1	100	0	.	0	.	61	35	198	26	31	40	36	19
	Arolla pine	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	111	66	68	31	29	77	22	35
	other conifers	58	69	0	.	9	100	67	49	72	59	0	.	0	.	21	100	0	.	0	.	0	.	0	.	0	.	1	100	22	34
	beech	10088	13	17316	18	11311	35	5316	18	8949	12	2163	41	3009	31	7693	27	5377	50	2906	57	4735	46	294	49	815	31	1444	34	5329	7
	maple	6314	17	15954	31	8362	33	4525	27	14974	18	3768	49	1708	29	7046	23	2250	31	1230	31	1077	43	331	30	375	39	402	25	4617	9
	ash	4379	20	6866	21	4232	26	3867	39	6626	16	2066	43	1866	27	4749	25	1566	30	2519	44	3151	31	4163	57	901	42	4014	31	3672	9
	oak	1194	47	2008	54	2589	35	198	43	825	40	0	.	41	59	128	46	0	.	0	.	0	.	565	28	13	53	408	56	548	19
	sweet chestnut	0	.	0	.	5	100	0	.	0	.	0	.	0	.	0	.	23	100	0	.	0	.	2	100	10	100	164	30	22	28
	other broadleaves	1968	17	1371	24	2399	37	867	26	2083	23	2640	35	1699	17	1088	17	3240	22	2211	25	1262	36	2883	35	1600	17	796	23	1794	8
	species not assessed in all inventories	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	total	26657	10	44796	18	31368	17	20664	15	38021	10	13610	22	11902	12	24976	15	15716	22	10176	23	11162	24	9942	27	5914	12	7569	19	18736	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. 1196580. Birmensdorf, Swiss Federal Research Institute WSL

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