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.

NFI4
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: 1000 n
evaluation area: stockable and accessible forest without shrub forest
grid: 1.4-km grid
state 2009/17
		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)	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	.
	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	113427	24	6924	54	87669	55	111363	42	101383	24	34970	41	154399	27	80484	32	62306	27	13226	31	10017	39	62910	16	166741	26	11074	34	1016893	10
	fir	128236	15	34452	36	31846	39	189836	19	254205	20	35238	27	90113	17	82192	23	14027	36	2988	79	5494	74	11730	32	10143	65	6249	39	896749	8
	pine	2524	100	0	.	789	100	0	.	789	100	0	.	836	100	0	.	0	.	788	100	0	.	3814	66	15756	33	774	100	26071	25
	larch	0	.	0	.	0	.	0	.	2524	100	0	.	0	.	0	.	0	.	0	.	0	.	29792	67	6293	39	2329	58	40937	50
	Arolla pine	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	20956	36	22533	45	0	.	43489	29
	other conifers	2337	57	793	100	0	.	0	.	1578	100	0	.	818	100	818	100	0	.	0	.	734	100	0	0	0	0	774	100	7853	35
	beech	1558331	19	562658	20	511475	44	266867	22	654446	16	85074	34	181624	21	279387	23	245847	59	40534	45	15565	44	185181	50	25757	36	79087	49	4691832	9
	maple	725951	15	458833	29	349224	57	267588	24	1449424	17	114166	40	94413	18	390923	24	55124	25	53342	35	18481	34	79396	50	28516	48	93436	27	4178817	9
	ash	685477	17	347970	19	223942	23	301139	30	1101309	13	70448	25	328543	28	355889	21	98560	38	79427	38	98575	26	186493	31	59644	30	560237	26	4497654	7
	oak	206586	49	3046	50	131873	73	22642	28	31320	66	1730	71	1642	71	818	100	0	.	790	100	0	.	40075	37	11481	63	29947	43	481951	30
	sweet chestnut	779	100	0	.	9136	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	790	100	0	.	26867	22	37573	29
	other broadleaves	172686	16	41692	23	35394	33	52839	39	109150	19	35730	23	98875	22	59797	21	73516	22	36675	25	15375	31	129796	21	132781	16	106872	16	1101179	6
	species not assessed in all inventories	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	total	3596336	11	1456367	17	1381347	25	1212273	14	3706127	10	377357	18	951264	13	1250309	15	549380	30	227771	22	164242	19	750933	19	479643	14	917647	18	17020997	5
height 40-129 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	37030	21	1916	56	27967	39	21341	21	33676	23	19968	25	78385	19	33764	26	34390	19	8925	25	12173	28	39805	19	90412	16	17801	38	457554	7
	fir	36242	21	13005	67	10417	45	44876	21	32641	28	3580	36	29249	29	10135	31	1656	47	846	58	0	.	5087	39	7671	82	1963	50	197369	11
	pine	303	100	0	.	0	.	587	71	606	100	0	.	531	71	903	74	583	100	285	100	0	.	3476	63	12053	31	2779	91	22105	23
	larch	0	.	0	.	284	100	0	.	1211	100	0	.	596	71	0	.	858	58	0	.	0	.	8193	33	18695	38	5016	41	34853	23
	Arolla pine	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	2809	40	8264	27	0	.	11073	23
	other conifers	0	0	0	.	568	100	548	100	554	71	0	.	0	.	0	.	0	0	0	.	0	0	0	0	0	0	0	.	1671	53
	beech	527322	11	257575	14	109346	23	114433	20	401769	16	85034	45	95586	26	132755	26	20784	35	17259	80	23968	40	7732	49	16221	33	4558	26	1814341	6
	maple	92504	15	88858	24	32814	41	32911	23	237243	20	18704	31	25388	22	46824	28	19097	33	5330	35	4539	37	9347	36	5086	35	7394	39	626039	9
	ash	96791	19	61950	23	22398	27	46884	25	218732	22	20047	28	51971	22	61468	26	13597	31	15810	40	12590	38	15975	26	7645	47	63820	24	709679	9
	oak	2678	59	1689	47	2892	45	3993	33	3595	33	0	.	328	100	0	.	0	.	285	100	0	.	5520	44	0	.	828	75	21807	17
	sweet chestnut	0	.	0	.	606	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	4572	32	5178	30
	other broadleaves	67537	22	19001	34	17072	31	25428	40	63708	18	21491	28	31062	16	30706	20	32214	19	14744	25	11592	39	33852	18	52490	20	29579	18	450477	6
	species not assessed in all inventories	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	total	860406	8	443994	12	224364	15	291001	12	993737	11	168823	26	313096	11	316555	15	123180	14	63484	27	64862	21	131795	11	218538	11	138309	14	4352145	4
DBH 0-3.9 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	15822	18	1176	52	4046	28	11765	24	12124	24	10590	22	27110	16	11563	22	13943	16	3735	26	4862	25	16235	15	33144	18	9037	19	175154	6
	fir	15803	15	1598	83	4829	37	16054	22	5256	34	1915	27	11029	22	6937	28	1189	35	299	58	102	100	5170	33	504	45	1665	34	72352	9
	pine	218	100	95	100	0	.	0	.	636	72	0	.	811	55	202	100	210	71	519	53	0	.	3759	41	9438	33	1003	100	16891	22
	larch	0	.	95	100	109	100	0	.	218	70	108	100	0	.	0	.	420	79	0	.	0	.	5135	24	13424	23	3207	26	22716	15
	Arolla pine	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	1423	32	2743	26	194	100	4361	20
	other conifers	101	100	0	.	0	.	218	70	492	54	0	.	0	0	0	0	0	0	0	.	0	0	0	0	0	0	0	0	811	40
	beech	252173	10	114406	18	46978	23	81717	23	193646	14	21187	39	65698	25	35556	18	10081	26	6049	45	8323	28	3376	36	7587	27	18653	59	865432	6
	maple	35635	14	28650	23	13699	50	14168	24	83996	18	5853	26	13540	20	13722	41	9137	26	2136	51	1019	47	2730	26	2635	38	2287	30	229209	9
	ash	39061	19	15625	23	12678	24	17931	33	56872	15	6265	40	32993	37	14780	34	4677	29	3952	43	5960	51	7971	27	2231	41	17927	49	238923	9
	oak	210	71	109	100	613	57	218	70	2006	44	0	.	202	100	118	100	0	.	0	.	0	.	524	53	0	.	298	58	4298	25
	sweet chestnut	0	.	0	.	109	100	0	.	0	.	0	.	0	.	0	.	0	.	102	100	0	.	102	100	0	.	3227	43	3540	39
	other broadleaves	26786	14	11012	28	15515	26	11226	25	26242	17	18025	21	22183	14	18792	28	23029	22	6270	23	5735	25	23050	29	17360	28	18695	14	243919	6
	species not assessed in all inventories	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	total	385810	8	172768	14	98576	16	153297	15	381489	10	63943	17	173566	13	101670	14	62685	13	23063	19	26002	20	69477	13	89066	11	76193	20	1877606	4
DBH 4-7.9 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	6251	15	1353	40	1790	21	6772	18	5876	18	4336	19	10908	11	5256	18	7881	18	2865	21	3438	21	9611	11	20445	11	7210	15	93993	4
	fir	8702	11	469	41	2940	28	4640	21	1566	26	882	27	4945	17	3082	29	419	43	900	28	186	53	2574	31	507	40	1369	33	33181	7
	pine	121	74	37	100	0	.	0	.	206	53	0	.	126	74	82	71	573	93	284	55	0	.	1999	25	4478	28	806	58	8711	17
	larch	0	.	151	61	0	.	318	89	78	71	0	.	0	.	39	100	204	83	0	.	0	.	3665	17	3927	22	2762	22	11144	11
	Arolla pine	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	41	100	0	.	1044	27	1314	28	0	.	2399	19
	other conifers	158	100	0	.	81	71	232	71	240	53	0	0	0	0	0	0	0	0	0	.	0	0	0	0	0	0	0	0	711	37
	beech	12447	13	6763	19	4530	25	7176	15	9756	14	1363	44	4967	15	3996	17	2477	29	588	47	2301	25	893	36	2001	41	4471	19	63728	5
	maple	4449	21	3425	24	1794	31	1394	24	6114	18	1450	37	1476	22	987	26	1718	33	480	47	403	35	1458	19	520	52	918	25	26584	8
	ash	3262	22	2345	29	1990	31	1641	39	5719	23	497	62	1628	28	1051	36	807	47	310	50	602	47	619	36	351	53	1562	26	22385	9
	oak	159	50	213	72	323	40	432	55	929	54	0	.	39	100	0	.	0	.	0	.	0	.	596	36	0	.	314	49	3005	22
	sweet chestnut	0	.	0	.	40	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	40	100	0	.	523	32	603	29
	other broadleaves	4957	13	1719	29	1922	24	1747	22	3436	20	2426	25	3436	16	2089	21	3832	18	1582	24	1129	30	6864	15	3608	28	9250	12	47997	5
	species not assessed in all inventories	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	total	40505	7	16475	14	15409	13	24353	10	33920	9	10955	14	27524	7	16583	12	17910	12	7049	16	8060	14	29362	7	37152	8	29183	7	314441	2
DBH 8-11.9 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	3794	17	940	35	740	26	4093	20	3541	16	1834	22	4812	13	2987	16	3924	16	1675	33	1948	23	5824	12	11539	9	4345	15	51995	4
	fir	5166	13	272	38	1158	23	2526	21	1229	27	510	34	2786	15	1396	28	345	40	459	35	231	47	1195	43	119	58	570	40	17963	7
	pine	39	100	43	100	0	.	78	71	256	70	0	.	252	71	0	.	324	67	120	75	40	100	846	26	2192	26	347	61	4537	16
	larch	39	100	37	100	128	100	43	100	43	100	0	.	0	.	39	100	204	45	0	.	0	.	1810	19	2397	22	1602	28	6343	13
	Arolla pine	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	82	100	0	.	361	49	999	28	0	.	1442	24
	other conifers	158	79	40	100	0	.	78	71	160	61	0	.	83	71	166	71	0	0	0	.	0	0	0	0	0	0	0	0	684	32
	beech	4483	14	2359	23	1053	26	3381	18	3491	17	714	37	2878	17	1476	20	1099	27	309	35	1026	38	469	33	505	41	2977	19	26220	6
	maple	1339	22	657	34	445	42	678	30	1195	22	563	38	591	26	678	39	632	26	199	45	239	47	920	24	79	71	652	36	8868	9
	ash	750	45	582	36	550	32	363	37	1667	20	204	54	336	47	494	31	233	70	198	60	204	53	313	35	120	75	969	29	6983	10
	oak	474	76	43	100	43	100	383	66	287	76	0	.	0	.	0	.	0	0	40	100	41	100	863	30	38	100	393	39	2604	22
	sweet chestnut	0	.	0	.	39	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	757	28	796	27
	other broadleaves	1924	18	952	25	704	27	1092	29	1740	20	921	34	1152	21	699	32	1361	29	669	42	662	35	3175	16	1448	23	6233	12	22733	6
	species not assessed in all inventories	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	total	18167	8	5925	15	4859	12	12714	11	13608	9	4746	15	12890	8	7936	11	8122	12	3750	19	4389	16	15779	8	19437	8	18845	7	151167	3
total	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	176323	17	12309	34	122212	45	155335	31	156601	17	71699	26	275613	18	134055	25	122444	17	30427	21	32438	20	134385	12	322281	17	49467	21	1795589	7
	fir	194150	13	49796	44	51189	30	257932	17	294897	18	42125	24	138122	16	103742	19	17637	30	5492	47	6013	68	25757	26	18944	48	11816	27	1217613	7
	pine	3206	96	175	79	789	100	665	63	2492	56	0	.	2556	56	1187	62	1689	61	1994	55	40	100	13895	34	43917	22	5709	82	78314	16
	larch	39	100	284	75	521	63	361	79	4074	92	108	100	596	71	79	71	1685	55	0	.	0	.	48595	46	44736	26	14916	23	115994	22
	Arolla pine	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	123	100	0	.	26593	32	35853	31	194	100	62763	22
	other conifers	2754	50	833	95	649	88	1076	55	3025	56	0	0	901	91	984	84	0	0	0	.	734	100	0	0	0	0	774	100	11731	25
	beech	2354756	13	943762	14	673381	34	473574	17	1263108	12	193372	35	350753	17	453170	20	280289	52	64740	47	51182	27	197651	47	52070	25	109745	37	7461552	7
	maple	859878	14	580424	24	397977	52	316738	21	1777973	15	140736	35	135408	15	453134	22	85708	20	61487	31	24681	29	93851	44	36836	39	104687	25	5069516	8
	ash	825341	15	428472	16	261559	21	367958	26	1384300	12	97461	22	415471	24	433682	19	117874	32	99698	36	117932	24	211372	27	69990	28	644514	24	5475623	6
	oak	210107	49	5100	36	135743	71	27668	25	38136	55	1730	71	2212	56	937	88	0	0	1115	75	41	100	47578	34	11519	63	31780	41	513665	28
	sweet chestnut	779	100	0	.	9929	93	0	.	0	.	0	.	0	.	0	.	0	.	102	100	0	.	933	86	0	.	35946	19	47689	24
	other broadleaves	273890	14	74375	20	70607	22	92331	34	204276	14	78594	18	156708	16	112084	16	133953	15	59940	20	34494	26	196737	16	207688	13	170629	12	1866305	5
	species not assessed in all inventories	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	total	4901224	8	2095530	13	1724556	21	1693638	11	5128881	9	625824	17	1478340	10	1693054	13	761278	22	325118	20	267555	15	997346	15	843836	10	1180177	15	23716355	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. 1196500. Birmensdorf, Swiss Federal Research Institute WSL

back