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: 1000 n
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)	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	94198	32	10907	59	15329	55	98621	42	74222	34	17752	41	118489	22	81030	34	72494	27	9886	43	9812	52	67543	25	82626	26	5866	71	758775	10
	fir	161873	18	24823	40	43854	36	152391	19	201523	20	55558	32	62122	22	157334	33	24684	40	2569	71	3864	73	10115	74	5290	62	8261	46	914261	9
	pine	1497	100	0	.	1537	100	0	.	0	.	0	.	0	.	0	.	1360	100	0	.	0	.	1360	100	6827	45	0	.	12582	33
	larch	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	47087	97	4080	74	2664	71	53831	85
	Arolla pine	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	6930	100	4287	100	2547	100	13764	62
	other conifers	8210	71	0	.	0	.	4066	57	5368	80	0	.	0	.	1403	100	0	.	0	.	0	.	0	.	0	.	0	.	19047	40
	beech	762345	20	289952	24	246555	47	176559	25	455266	20	29132	47	120316	51	339108	38	242417	55	19349	48	104685	59	21522	53	52075	39	140969	36	3000249	10
	maple	789590	19	567364	32	260719	34	252703	32	1178355	22	103734	53	156629	36	430171	26	94650	39	19048	42	27202	48	23714	36	52701	38	45616	27	4002196	10
	ash	595118	20	254876	24	138251	29	234296	45	542805	17	59917	52	113871	32	299123	27	71730	33	45780	47	76179	36	394550	57	101714	42	469365	28	3397576	10
	oak	170509	48	81983	54	84057	37	12273	51	80338	42	0	.	3036	71	8648	47	0	.	0	.	0	.	44335	29	0	.	49569	56	534750	20
	sweet chestnut	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	1209	100	0	.	0	.	0	.	1209	100	15045	40	17463	36
	other broadleaves	186457	22	26030	33	54391	57	29713	33	112710	40	61192	34	87259	24	45865	24	121545	24	35491	29	26101	49	263600	38	168971	17	65369	25	1284692	10
	species not assessed in all inventories	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	total	2769797	13	1255936	21	844694	20	960623	20	2650585	13	327285	27	661721	17	1362682	18	630090	28	132124	26	247843	31	880756	30	479779	15	805271	19	14009186	5
height 40-129 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	37742	32	1957	50	19205	63	54996	62	60393	36	20702	35	72064	23	26067	26	46759	25	10501	34	4947	41	40288	29	112416	22	5623	35	513659	11
	fir	41635	29	3492	51	3412	43	72945	25	83251	26	6200	32	33784	35	9371	29	8001	46	499	100	1010	71	3015	53	499	100	2429	60	269542	12
	pine	539	100	0	.	1406	74	473	100	0	.	0	.	506	100	0	.	490	100	0	.	0	.	6384	86	9456	63	458	100	19712	42
	larch	0	.	0	.	0	.	0	.	553	100	0	.	0	.	0	.	0	.	0	.	0	.	14281	87	12618	36	917	70	28370	47
	Arolla pine	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	3521	52	4955	40	917	100	9393	30
	other conifers	0	.	0	.	0	.	469	100	942	71	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	1410	58
	beech	431523	14	265615	29	155757	31	142150	27	230296	17	34548	45	79210	39	122065	28	64259	33	14091	70	16278	29	7403	49	26405	44	28644	60	1618245	8
	maple	82023	29	82031	49	66931	51	45573	30	267415	23	34023	64	23414	32	56796	36	21248	24	5540	45	2947	53	4974	49	2525	60	6401	33	701840	13
	ash	42322	23	19771	35	29050	37	40155	29	127633	20	18148	48	40329	40	27558	33	12698	39	9788	57	7964	50	13012	35	16697	48	58371	45	463496	10
	oak	971	71	0	.	14649	87	2083	50	2855	47	0	.	588	100	0	.	0	.	0	.	0	.	7024	39	1512	58	3469	59	33150	40
	sweet chestnut	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	3626	43	3626	43
	other broadleaves	65944	20	21848	31	26698	27	17870	34	67065	22	27138	65	46276	23	20518	21	48579	29	14367	35	4753	39	39560	24	50905	28	34579	31	486099	8
	species not assessed in all inventories	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	total	702698	11	394712	27	317109	22	376714	18	840402	13	140759	29	296170	16	262374	18	202033	17	54786	29	37900	22	139462	18	237988	16	145433	23	4148541	5
DBH 0-3.9 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	15034	25	883	66	6454	44	8560	28	11525	20	12524	33	23858	16	11670	23	18980	22	2696	40	4109	53	16926	24	42327	21	5258	34	180805	8
	fir	13468	22	7632	98	1699	58	32163	29	21878	33	2069	38	8587	41	5861	37	1048	47	739	50	529	74	3822	39	550	75	3039	32	103085	14
	pine	194	100	177	100	169	100	176	100	0	.	0	.	0	.	0	.	0	.	529	100	176	100	2485	48	6396	36	844	81	11145	25
	larch	0	.	177	100	537	73	0	.	399	100	0	.	0	.	0	.	187	100	0	.	0	.	5232	40	7764	28	2554	49	16850	20
	Arolla pine	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	1081	47	2515	30	0	.	3595	25
	other conifers	177	100	0	.	199	100	199	100	852	66	0	.	0	0	0	.	0	0	0	.	0	0	0	0	0	0	184	100	1612	42
	beech	253301	14	134212	21	47587	50	68295	22	215940	16	22185	47	71062	31	64767	22	13854	31	31196	89	7743	29	3791	55	23086	47	11727	39	968743	8
	maple	35474	22	13911	25	5433	39	29183	39	90658	20	8663	29	17436	26	23174	34	6074	27	4208	58	520	58	3902	39	1986	62	1635	48	242259	10
	ash	6454	25	3547	38	2685	44	4782	41	15442	29	1539	50	21222	54	3249	53	2456	66	1339	63	2465	55	3803	43	3974	50	2590	34	75547	18
	oak	194	100	0	.	4610	65	1256	38	1076	53	0	.	177	100	0	.	0	.	0	.	0	.	2115	70	176	100	165	100	9770	35
	sweet chestnut	0	.	0	.	199	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	188	100	0	.	3489	29	3876	27
	other broadleaves	30906	21	6836	43	12879	42	11446	35	29957	22	17014	26	25878	21	13039	28	20621	23	8925	26	3518	37	20783	22	13719	26	13682	20	229202	7
	species not assessed in all inventories	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	0	0	0	0
	total	355202	11	167375	19	82451	31	156059	16	387728	11	63995	23	168219	16	121760	16	63221	15	49632	57	19060	26	64129	14	102492	15	45167	14	1846490	5
DBH 4-7.9 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	6467	21	691	51	1783	38	4403	25	5366	21	6622	26	9859	15	5736	24	8610	20	2956	26	3142	41	8123	18	18236	19	5676	23	87670	6
	fir	7252	15	1109	82	1222	39	6346	21	2788	37	1041	32	3985	24	2936	34	342	53	620	39	61	100	1922	37	203	58	1214	45	31042	9
	pine	76	100	0	.	0	.	0	.	156	70	0	.	138	100	0	.	0	.	72	100	0	.	1741	36	3739	40	774	71	6695	26
	larch	0	.	69	100	66	100	0	.	378	84	0	.	0	.	0	.	351	60	0	.	0	.	2375	28	2256	28	2108	28	7604	15
	Arolla pine	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	991	36	1677	37	64	100	2733	26
	other conifers	0	.	0	.	156	100	69	100	222	58	0	.	0	.	0	.	0	0	0	0	0	0	0	0	0	0	0	0	446	47
	beech	14656	15	7599	24	1319	32	6645	22	13394	18	868	36	5526	20	4447	25	1478	29	1229	44	1859	40	1107	66	1180	40	4303	35	65609	7
	maple	5118	19	1959	30	589	46	1155	30	5728	21	1009	34	1470	32	1162	30	1808	36	423	58	207	74	1331	29	484	43	652	37	23094	9
	ash	1208	35	580	50	487	43	1311	56	2146	32	562	73	1739	53	314	50	611	36	0	.	406	47	563	66	354	66	668	40	10950	15
	oak	69	100	0	.	156	70	78	100	291	50	0	.	0	.	0	.	0	.	0	.	0	.	278	61	0	.	280	62	1151	28
	sweet chestnut	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	676	36	676	36
	other broadleaves	4169	20	1825	28	1618	29	2810	25	4138	19	3314	30	3004	22	2614	29	4215	22	2571	31	632	43	7300	27	3701	35	9341	17	51251	7
	species not assessed in all inventories	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	0	0	0	0
	total	39015	9	13830	18	7395	16	22816	13	34608	11	13415	17	25720	11	17209	15	17416	15	7872	21	6306	27	25732	12	31831	13	25757	11	288921	3
DBH 8-11.9 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	2110	21	825	42	958	39	3921	24	2515	23	2675	26	4325	17	2367	24	3842	21	1693	31	2111	32	3709	18	10892	15	3723	26	45666	6
	fir	4903	18	347	66	691	47	1905	29	1173	36	216	58	2986	23	1640	39	285	62	469	38	208	58	996	39	143	71	714	45	16675	10
	pine	0	.	69	100	0	.	78	100	222	76	0	.	0	.	0	.	0	.	289	79	0	.	1405	35	1806	32	709	73	4579	21
	larch	68	100	69	100	78	100	78	100	156	100	174	100	0	.	60	100	421	70	0	.	0	.	1772	22	1338	32	1959	32	6172	15
	Arolla pine	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	354	60	1477	30	0	.	1831	27
	other conifers	69	100	0	.	0	.	78	100	0	0	0	.	0	0	0	.	0	0	0	.	0	0	0	.	0	0	0	0	147	71
	beech	5576	16	3345	22	1118	34	2925	24	4528	18	296	50	2995	23	1305	29	549	49	562	40	975	48	122	100	219	74	3644	23	28160	7
	maple	2132	23	1074	33	725	49	413	41	1515	25	559	78	661	38	450	46	763	43	69	100	487	43	849	31	510	88	491	47	10699	11
	ash	777	57	203	74	203	75	415	57	333	53	496	89	235	79	71	100	624	71	70	100	138	71	424	47	138	100	442	41	4567	20
	oak	956	79	145	71	78	100	78	100	611	56	0	.	71	100	0	.	0	.	0	.	0	0	628	46	0	.	136	71	2703	33
	sweet chestnut	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	365	45	365	45
	other broadleaves	1963	23	551	56	784	39	1337	27	2257	20	1042	38	1707	31	974	37	917	33	1133	45	482	43	3306	20	1879	44	5608	16	23940	8
	species not assessed in all inventories	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	0	0	0	0
	total	18553	10	6627	17	4636	20	11227	14	13309	11	5458	19	12979	11	6867	16	7402	17	4285	22	4400	21	13566	11	18404	11	17791	10	145505	3
total	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	155550	22	15263	43	43730	49	170500	38	154021	28	60275	26	228595	17	126870	24	150686	19	27733	27	24121	30	136589	19	266497	17	26145	25	1586575	7
	fir	229131	15	37403	38	50879	32	265751	17	310613	17	65084	28	111462	20	177142	30	34361	36	4897	41	5671	52	19871	41	6685	50	15657	30	1334606	8
	pine	2306	100	246	100	3112	60	726	70	378	67	0	.	644	81	0	.	1850	78	891	65	176	100	13375	57	28223	33	2785	66	54713	23
	larch	68	100	315	71	681	67	78	100	1485	96	174	100	0	.	60	100	959	56	0	.	0	.	70747	82	28057	24	10202	27	112827	52
	Arolla pine	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	12877	56	14911	38	3529	77	31317	31
	other conifers	8457	69	0	.	355	100	4880	49	7384	59	0	.	0	0	1403	100	0	0	0	0	0	0	0	0	0	0	184	100	22662	34
	beech	1467400	13	700722	20	452335	36	396574	19	919424	13	87028	40	279108	32	531691	27	322558	46	66427	57	131540	47	33946	43	102965	31	189287	32	5681006	7
	maple	914337	17	666339	31	334398	34	329028	27	1543671	19	147988	49	199609	30	511753	22	124544	31	29288	32	31363	42	34771	29	58206	36	54795	23	4980088	9
	ash	645879	19	278977	22	170676	27	280959	39	688358	16	80663	44	177395	26	330315	25	88119	29	56977	46	87152	32	412352	55	122876	40	531437	29	3952135	9
	oak	172700	47	82128	53	103549	36	15767	41	85172	40	0	.	3872	58	8648	47	0	.	0	.	0	0	54380	29	1688	53	53619	53	581524	19
	sweet chestnut	0	.	0	.	199	100	0	.	0	.	0	.	0	.	0	.	1209	100	0	.	0	.	188	100	1209	100	23201	28	26007	26
	other broadleaves	289440	17	57089	25	96370	38	63175	27	216126	23	109699	34	164125	17	83009	17	195877	21	62486	24	35485	37	334549	31	239175	15	128579	19	2075185	7
	species not assessed in all inventories	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	0	0	0	0
	total	3885266	10	1838481	19	1256285	19	1527439	15	3926632	11	550912	23	1164810	12	1770892	15	920162	21	248699	24	315510	25	1123644	25	870494	12	1039419	17	20438644	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. 1196523. Birmensdorf, Swiss Federal Research Institute WSL

back