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
total number of stems
tree state (living/dead) · diameter at breast height (10 classes)
regional demarcation: canton
unit: 1000 n
evaluation area: accessible forest without shrub forest NFI1-NFI5
grid: 1.4 km grid, subgrids 1-5
state 2018/26
		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 state (living/dead)	diameter at breast height (10 classes)	1000 n	±%	1000 n	±%	1000 n	±%	1000 n	±%	1000 n	±%	1000 n	±%	1000 n	±%	1000 n	±%	1000 n	±%	1000 n	±%	1000 n	±%	1000 n	±%	1000 n	±%	1000 n	±%	1000 n	±%	1000 n	±%	1000 n	±%	1000 n	±%	1000 n	±%	1000 n	±%	1000 n	±%	1000 n	±%	1000 n	±%	1000 n	±%	1000 n	±%	1000 n	±%
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	.
	12-20 cm	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	.
	21-30 cm	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	.
	31-40 cm	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	.
	41-50 cm	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	.
	51-60 cm	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	.
	61-70 cm	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	.
	71-80 cm	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	.
	81-90 cm	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	.
	91-100 cm	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	.
	>100 cm	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	.
living	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	.
	12-20 cm	5532	14	257	37	1099	33	26895	7	3238	21	5560	15	190	61	1706	25	23334	8	4624	14	8712	13	4767	15	1561	37	4079	22	7194	15	1773	27	5176	18	3327	22	3528	17	23683	8	3238	21	15578	10	18513	8	408	38	6537	14	180509	2
	21-30 cm	2953	15	367	38	933	29	15109	7	1454	20	4127	14	121	65	1148	24	14240	7	2424	15	4357	12	2887	14	1272	34	2516	21	4950	14	1067	24	2654	15	2051	20	2299	17	14386	7	2429	19	7921	10	10985	9	419	37	3794	14	106866	2
	31-40 cm	1415	16	590	29	828	26	9565	7	1010	20	2780	14	110	60	669	23	9141	7	1723	16	2680	13	1455	18	766	33	1560	21	3423	12	848	23	1902	17	1471	18	1325	21	6318	9	1389	21	5115	9	5879	9	293	35	2342	12	64597	2
	41-50 cm	1118	14	405	29	445	27	6421	6	506	22	1646	13	57	58	599	22	5900	6	1418	15	1643	12	1164	13	337	32	776	20	2000	12	534	21	1102	15	1040	17	751	18	3094	8	788	23	3446	9	3469	9	184	38	1656	12	40500	2
	51-60 cm	699	15	249	33	371	30	4055	7	311	23	1050	14	22	100	390	23	3439	7	721	16	1346	13	722	15	97	39	411	24	1328	12	189	25	564	18	743	16	429	19	1663	14	338	24	1776	10	2027	10	80	36	993	13	24013	2
	61-70 cm	259	20	106	36	91	42	1724	9	91	33	305	18	7	100	164	30	1439	9	339	20	511	18	281	23	91	42	119	36	678	17	121	29	148	30	262	25	220	23	576	13	164	27	941	13	835	13	28	71	459	17	9961	3
	71-80 cm	185	21	22	58	36	45	699	12	57	43	162	25	7	100	106	41	599	12	101	36	199	23	141	23	19	58	111	38	318	20	51	42	75	39	128	32	60	45	318	19	64	46	291	18	398	19	14	71	177	24	4338	5
	81-90 cm	53	39	7	100	0	.	203	21	7	100	62	39	0	.	27	50	272	20	15	71	28	50	60	39	0	.	21	77	133	26	0	.	14	71	35	51	55	43	115	27	32	51	60	36	128	28	0	.	65	34	1393	8
	91-100 cm	20	58	0	.	0	.	74	32	0	.	0	.	0	.	35	45	85	31	7	100	0	.	8	100	0	.	0	.	26	60	0	.	7	100	14	71	21	58	59	46	0	.	23	58	73	31	0	.	14	71	465	13
	>100 cm	0	.	0	.	0	.	35	45	0	.	7	100	0	.	7	100	44	41	14	71	7	100	8	100	0	.	0	.	14	71	0	.	0	.	7	100	16	100	69	45	0	.	7	100	14	71	0	.	0	.	251	20
	total	12234	11	2003	29	3803	24	64780	5	6674	16	15699	11	515	54	4852	19	58492	6	11387	12	19483	10	11493	11	4143	30	9593	17	20065	11	4584	19	11641	13	9080	14	8705	14	50282	6	8442	17	35159	8	42322	7	1426	32	16036	10	432892	2
dead	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	.
	12-20 cm	622	25	249	44	236	37	3856	11	554	27	1519	20	71	50	768	37	5206	11	1159	21	1680	21	711	22	151	50	779	33	1553	17	246	33	699	24	884	27	339	33	6380	11	719	30	2692	13	4970	12	180	45	941	28	37166	4
	21-30 cm	243	28	15	100	281	28	1921	13	225	37	507	26	17	100	311	33	2748	12	396	27	824	28	72	50	158	39	225	32	729	22	87	53	465	26	532	35	136	47	1751	14	328	27	999	19	1708	14	54	74	530	28	15263	5
	31-40 cm	55	49	15	100	154	44	1458	14	120	33	254	33	0	.	136	40	1318	15	406	41	316	23	146	34	67	45	156	52	385	25	43	41	126	41	146	40	41	85	593	20	117	43	498	21	1104	14	38	83	116	29	7807	6
	41-50 cm	94	32	14	71	30	50	643	14	57	39	158	26	7	100	67	42	640	16	92	33	177	25	35	45	31	81	107	35	198	23	63	81	83	35	97	36	42	41	315	18	59	46	220	24	430	15	7	100	76	35	3744	6
	51-60 cm	70	38	6	100	29	79	357	17	28	71	108	42	0	.	34	54	433	16	28	50	44	46	22	58	13	71	24	60	73	35	21	74	14	70	61	43	13	71	153	35	46	41	119	29	245	20	14	100	49	43	2003	7
	61-70 cm	36	54	0	.	7	100	93	30	7	100	41	52	0	.	7	100	112	25	15	71	104	39	0	.	0	.	26	50	28	50	7	100	21	58	0	.	7	100	76	47	36	45	37	45	84	29	0	.	13	100	756	11
	71-80 cm	7	100	0	.	0	.	62	40	7	100	33	58	0	.	0	.	13	71	14	70	23	59	0	.	0	.	0	.	22	58	0	.	0	.	7	100	0	.	67	40	0	.	14	71	22	58	0	.	13	71	304	17
	81-90 cm	0	.	0	.	0	.	13	71	0	.	0	.	0	.	0	.	21	58	0	.	0	.	0	.	0	.	0	.	6	100	0	.	0	.	0	.	0	.	15	71	0	.	7	100	7	100	0	.	0	.	70	32
	91-100 cm	0	.	0	.	0	.	7	100	0	.	0	.	0	.	7	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	8	100	0	.	0	.	7	100	0	.	0	.	29	50
	>100 cm	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	7	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	7	100
	total	1126	18	299	42	736	28	8409	9	998	23	2620	17	95	52	1330	29	10492	9	2110	19	3169	17	994	19	421	34	1317	27	2993	14	467	30	1408	20	1727	25	579	32	9357	9	1304	23	4587	11	8577	10	293	35	1739	23	67148	3
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	.
	12-20 cm	6154	14	506	39	1335	30	30750	6	3792	20	7079	14	261	52	2473	23	28540	7	5784	14	10392	13	5478	15	1713	38	4859	21	8746	14	2019	26	5875	17	4211	20	3867	17	30063	7	3957	21	18270	9	23483	8	588	36	7478	14	217675	2
	21-30 cm	3196	14	382	37	1214	26	17030	7	1679	20	4634	13	138	61	1460	23	16988	7	2820	15	5182	12	2959	14	1430	32	2742	20	5680	13	1154	24	3120	15	2584	20	2436	17	16137	7	2756	19	8920	10	12693	9	472	36	4325	13	122129	2
	31-40 cm	1469	16	605	29	981	25	11022	6	1130	19	3035	14	110	60	805	23	10460	6	2130	16	2996	12	1601	17	832	31	1715	22	3809	12	891	23	2027	17	1617	18	1366	21	6910	9	1506	20	5613	9	6983	8	331	33	2458	12	72404	2
	41-50 cm	1212	14	419	29	475	26	7064	6	564	22	1804	13	64	57	666	21	6540	6	1510	15	1819	12	1200	13	368	31	883	20	2198	12	597	21	1185	15	1138	17	794	17	3409	8	847	23	3666	9	3899	9	191	37	1731	11	44244	2
	51-60 cm	769	15	255	32	400	29	4412	6	338	22	1157	14	22	100	424	24	3872	7	749	16	1390	13	744	15	110	36	435	23	1401	12	210	24	578	18	804	16	443	19	1816	14	383	22	1895	9	2272	9	95	34	1042	12	26016	2
	61-70 cm	295	19	106	36	98	40	1817	9	98	33	346	17	7	100	171	31	1551	9	354	19	616	17	281	23	91	42	145	32	706	17	127	29	169	27	262	25	227	23	652	12	200	28	978	13	919	13	28	71	472	17	10717	3
	71-80 cm	191	21	22	58	36	45	761	11	64	39	195	23	7	100	106	41	612	12	115	33	223	21	141	23	19	58	111	38	339	20	51	42	75	39	135	31	60	45	385	17	64	46	305	17	419	18	14	71	190	23	4641	5
	81-90 cm	53	39	7	100	0	.	216	20	7	100	62	39	0	.	27	50	293	20	15	71	28	50	60	39	0	.	21	77	140	26	0	.	14	71	35	51	55	43	130	27	32	51	67	34	136	27	0	.	65	34	1462	8
	91-100 cm	20	58	0	.	0	.	81	30	0	.	0	.	0	.	42	41	85	31	7	100	0	.	8	100	0	.	0	.	26	60	0	.	7	100	14	71	21	58	67	42	0	.	23	58	80	30	0	.	14	71	494	13
	>100 cm	0	.	0	.	0	.	35	45	0	.	7	100	0	.	7	100	44	41	14	71	7	100	15	71	0	.	0	.	14	71	0	.	0	.	7	100	16	100	69	45	0	.	7	100	14	71	0	.	0	.	258	19
	total	13360	11	2302	29	4540	22	73189	5	7672	16	18320	11	610	52	6182	19	68984	6	13497	12	22652	10	12487	11	4564	29	10910	17	23058	10	5050	19	13050	13	10807	14	9285	14	59639	6	9746	17	39745	8	50898	7	1719	31	17775	10	500040	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. 1230429. Birmensdorf, Swiss Federal Research Institute WSL

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