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
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	625	32	262	58	370	54	1320	42	702	34	417	40	1192	22	1098	33	1140	26	328	42	297	51	563	25	546	26	38	71	641	10
	fir	1074	18	597	39	1059	35	2039	18	1905	20	1305	31	625	22	2132	33	388	40	85	70	117	72	84	74	35	62	53	46	772	9
	pine	10	100	0	.	37	100	0	.	0	.	0	.	0	.	0	.	21	100	0	.	0	.	11	100	45	44	0	.	11	33
	larch	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	392	97	27	74	17	71	45	85
	Arolla pine	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	58	100	28	100	16	100	12	62
	other conifers	54	71	0	.	0	.	54	57	51	79	0	.	0	.	19	100	0	.	0	.	0	.	0	.	0	.	0	.	16	40
	beech	5057	20	6971	23	5954	47	2363	25	4304	20	684	47	1210	51	4594	38	3813	55	643	47	3173	58	179	53	344	39	902	36	2533	10
	maple	5237	19	13640	31	6296	33	3382	31	11140	22	2437	52	1576	35	5828	25	1489	39	633	41	825	47	198	36	348	38	292	27	3379	10
	ash	3947	20	6127	22	3338	28	3135	45	5132	16	1408	52	1146	32	4052	26	1128	33	1521	46	2309	35	3286	57	672	42	3002	28	2869	10
	oak	1131	47	1971	53	2030	36	164	50	760	42	0	.	31	71	117	46	0	.	0	.	0	.	369	29	0	.	317	56	451	20
	sweet chestnut	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	19	100	0	.	0	.	0	.	8	100	96	40	15	36
	other broadleaves	1237	22	626	32	1313	56	398	33	1066	40	1437	33	878	24	621	23	1912	23	1179	27	791	48	2196	38	1117	17	418	25	1085	10
	species not assessed in all inventories	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	total	18372	13	30193	20	20397	19	12855	19	25059	12	7688	25	6657	16	18461	17	9911	27	4389	24	7512	30	7336	30	3171	14	5151	19	11828	5
height 40-129 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	250	32	47	49	464	63	736	62	571	35	486	34	725	22	353	25	735	24	349	32	150	40	336	28	743	22	36	35	434	11
	fir	276	28	84	51	82	42	976	25	787	26	146	31	340	35	127	28	126	45	17	99	31	70	25	53	3	100	16	60	228	12
	pine	4	100	0	.	34	74	6	100	0	.	0	.	5	100	0	.	8	100	0	.	0	.	53	86	62	63	3	100	17	42
	larch	0	.	0	.	0	.	0	.	5	100	0	.	0	.	0	.	0	.	0	.	0	.	119	87	83	36	6	70	24	47
	Arolla pine	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	29	52	33	39	6	100	8	30
	other conifers	0	.	0	.	0	.	6	100	9	71	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	1	58
	beech	2862	14	6386	28	3761	30	1902	26	2177	16	812	45	797	39	1654	28	1011	32	468	69	493	28	62	49	175	44	183	60	1366	8
	maple	544	29	1972	48	1616	50	610	30	2528	23	799	64	236	32	769	35	334	24	184	44	89	52	41	49	17	60	41	33	593	13
	ash	281	23	475	34	701	36	537	29	1207	19	426	47	406	40	373	33	200	39	325	56	241	49	108	34	110	48	373	45	391	10
	oak	6	71	0	.	354	86	28	50	27	47	0	.	6	100	0	.	0	.	0	.	0	.	59	39	10	58	22	59	28	40
	sweet chestnut	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	23	42	3	43
	other broadleaves	437	20	525	30	645	26	239	34	634	21	638	64	466	23	278	20	764	29	477	34	144	38	330	23	336	28	221	31	410	8
	species not assessed in all inventories	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	total	4661	10	9489	26	7657	20	5041	17	7945	12	3307	28	2979	15	3555	17	3178	16	1820	27	1149	20	1162	17	1573	15	930	23	3503	5
DBH 0-3.9 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	100	25	21	66	156	43	115	28	109	20	294	32	240	15	158	22	299	21	90	39	125	52	141	23	280	20	34	34	153	7
	fir	89	22	183	97	41	58	430	28	207	33	49	38	86	41	79	36	16	47	25	49	16	74	32	39	4	75	19	31	87	14
	pine	1	100	4	100	4	100	2	100	0	.	0	.	0	.	0	.	0	.	18	99	5	99	21	48	42	36	5	81	9	25
	larch	0	.	4	100	13	73	0	.	4	100	0	.	0	.	0	.	3	100	0	.	0	.	44	39	51	28	16	48	14	20
	Arolla pine	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	9	47	17	30	0	.	3	25
	other conifers	1	100	0	.	5	100	3	100	8	66	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	1	100	1	42
	beech	1680	14	3227	19	1149	49	914	22	2042	15	521	46	715	30	877	22	218	31	1036	88	235	28	32	55	153	47	75	39	818	8
	maple	235	22	334	23	131	38	391	38	857	20	204	27	175	25	314	33	96	26	140	57	16	57	33	39	13	62	10	48	205	10
	ash	43	24	85	38	65	43	64	40	146	29	36	49	213	54	44	52	39	66	44	63	75	54	32	43	26	50	17	34	64	18
	oak	1	100	0	.	111	65	17	37	10	53	0	.	2	100	0	.	0	.	0	.	0	.	18	69	1	100	1	100	8	35
	sweet chestnut	0	.	0	.	5	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	2	100	0	.	22	29	3	27
	other broadleaves	205	21	164	42	311	41	153	35	283	22	400	25	260	20	177	27	324	22	296	23	107	36	173	22	91	25	88	20	194	7
	species not assessed in all inventories	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	total	2356	11	4024	17	1991	30	2088	15	3666	11	1503	21	1692	15	1650	15	994	13	1649	56	578	24	534	13	677	15	289	14	1559	5
DBH 4-7.9 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	43	20	17	50	43	37	59	24	51	21	156	25	99	14	78	23	135	19	98	24	95	40	68	18	121	18	36	23	74	6
	fir	48	15	27	82	30	38	85	21	26	37	24	31	40	24	40	34	5	53	21	38	2	100	16	37	1	58	8	45	26	9
	pine	1	100	0	.	0	.	0	.	1	70	0	.	1	100	0	.	0	.	2	99	0	.	15	36	25	39	5	71	6	26
	larch	0	.	2	100	2	100	0	.	4	84	0	.	0	.	0	.	6	60	0	.	0	.	20	27	15	28	13	27	6	15
	Arolla pine	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	8	36	11	37	0	100	2	26
	other conifers	0	.	0	.	4	100	1	100	2	57	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	47
	beech	97	14	183	22	32	31	89	21	127	18	20	35	56	20	60	24	23	28	41	43	56	38	9	65	8	40	28	35	55	7
	maple	34	19	47	29	14	45	15	30	54	21	24	33	15	32	16	30	28	35	14	57	6	74	11	29	3	43	4	37	19	9
	ash	8	35	14	50	12	42	18	55	20	31	13	72	17	53	4	50	10	36	0	.	12	46	5	66	2	66	4	40	9	15
	oak	0	100	0	.	4	70	1	100	3	50	0	.	0	.	0	.	0	.	0	.	0	.	2	61	0	.	2	62	1	28
	sweet chestnut	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	4	36	1	36
	other broadleaves	28	20	44	27	39	28	38	25	39	18	78	29	30	21	35	28	66	21	85	29	19	41	61	27	24	35	60	17	43	7
	species not assessed in all inventories	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	total	259	8	332	16	179	14	305	11	327	10	315	15	259	10	233	13	274	13	262	18	191	25	214	12	210	12	165	11	244	3
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	20	41	23	38	52	23	24	23	63	25	44	17	32	23	60	20	56	29	64	30	31	17	72	14	24	26	39	6
	fir	33	18	8	66	17	46	25	29	11	36	5	58	30	23	22	38	4	61	16	36	6	57	8	39	1	71	5	44	14	10
	pine	0	.	2	100	0	.	1	100	2	76	0	.	0	.	0	.	0	.	10	78	0	.	12	34	12	32	5	73	4	21
	larch	0	100	2	100	2	100	1	100	1	100	4	100	0	.	1	100	7	69	0	.	0	.	15	22	9	32	13	32	5	15
	Arolla pine	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	3	60	10	30	0	.	2	27
	other conifers	0	100	0	.	0	.	1	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	71
	beech	37	16	80	20	27	33	39	23	43	17	7	49	30	22	18	28	9	49	19	38	30	47	1	100	1	74	23	23	24	7
	maple	14	23	26	32	18	48	6	40	14	24	13	78	7	38	6	46	12	43	2	99	15	41	7	31	3	87	3	47	9	11
	ash	5	57	5	74	5	74	6	56	3	53	12	88	2	78	1	100	10	70	2	99	4	70	4	47	1	100	3	41	4	20
	oak	6	79	3	70	2	100	1	100	6	56	0	.	1	100	0	.	0	.	0	.	0	.	5	46	0	.	1	71	2	33
	sweet chestnut	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	2	45	0	45
	other broadleaves	13	23	13	55	19	38	18	26	21	20	24	37	17	31	13	36	14	33	38	43	15	41	28	19	12	44	36	16	20	8
	species not assessed in all inventories	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	total	123	10	159	14	112	18	150	13	126	10	128	17	131	10	93	14	116	15	142	20	133	18	113	10	122	11	114	10	123	3
total	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	1032	22	367	43	1056	48	2282	37	1456	28	1416	24	2300	16	1719	23	2370	18	921	24	731	28	1138	18	1761	17	167	25	1340	7
	fir	1520	15	899	37	1229	31	3556	16	2937	17	1529	27	1121	19	2400	30	540	35	163	40	172	51	166	41	44	50	100	30	1127	8
	pine	15	100	6	100	75	59	10	70	4	67	0	.	6	81	0	.	29	78	30	64	5	99	111	57	187	33	18	66	46	23
	larch	0	100	8	71	16	67	1	100	14	95	4	100	0	.	1	100	15	56	0	.	0	.	589	82	185	24	65	27	95	52
	Arolla pine	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	107	56	99	38	23	77	26	31
	other conifers	56	69	0	.	9	100	65	49	70	59	0	.	0	.	19	100	0	.	0	.	0	.	0	.	0	.	1	100	19	34
	beech	9733	13	16846	18	10923	35	5307	18	8692	12	2044	39	2808	31	7203	27	5074	46	2207	56	3987	46	283	43	680	31	1211	32	4796	7
	maple	6065	17	16019	30	8075	33	4403	27	14594	18	3476	48	2008	29	6933	22	1959	31	973	30	951	41	290	28	385	36	350	23	4205	9
	ash	4284	19	6707	21	4121	26	3760	39	6508	15	1895	43	1785	26	4475	24	1386	28	1893	45	2642	31	3435	55	812	39	3399	29	3337	9
	oak	1146	47	1974	53	2500	35	211	40	805	40	0	.	39	57	117	46	0	.	0	.	0	.	453	28	11	53	343	53	491	19
	sweet chestnut	0	.	0	.	5	100	0	.	0	.	0	.	0	.	0	.	19	100	0	.	0	.	2	100	8	100	148	28	22	25
	other broadleaves	1920	17	1372	23	2327	37	845	26	2043	23	2577	33	1651	17	1125	16	3081	20	2076	22	1076	36	2787	30	1581	15	822	19	1752	7
	species not assessed in all inventories	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	total	25771	10	44198	17	30335	17	20440	14	37123	10	12942	21	11718	12	23991	14	14474	20	8262	22	9564	24	9359	25	5753	11	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. 1196586. Birmensdorf, Swiss Federal Research Institute WSL

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