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 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)	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	12297	39	108861	23	76812	35	71134	28	9886	43	7040	60	56249	26	73036	27	5866	71	714456	11
	fir	160428	18	23490	42	43854	36	142905	19	197214	21	52830	34	62122	22	151483	35	23475	42	2569	71	3864	73	8670	85	1209	100	5714	50	879825	9
	pine	1497	100	0	.	1537	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	1360	100	5467	50	0	.	9861	38
	larch	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	4080	74	1274	100	5354	62
	Arolla pine	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	6930	100	0	.	2547	100	9478	78
	other conifers	8210	71	0	.	0	.	4066	57	5368	80	0	.	0	.	1403	100	0	.	0	.	0	.	0	.	0	.	0	.	19047	40
	beech	760982	20	287226	24	246555	47	173902	26	455266	20	26405	52	118913	52	337917	39	225487	59	19349	48	104685	59	21522	53	52075	39	131747	39	2962031	10
	maple	789590	19	545559	33	260719	34	252703	32	1175644	22	103734	53	117660	36	409090	27	94650	39	19048	42	27202	48	22354	38	42586	41	41503	29	3902043	10
	ash	585579	21	252068	24	136949	29	234296	45	537384	17	59917	52	112464	32	293540	27	67663	35	45780	47	76179	36	384616	58	94828	45	435288	30	3316552	10
	oak	170509	48	80621	54	84057	37	10918	56	80338	42	0	.	3036	71	8648	47	0	.	0	.	0	.	44335	29	0	.	48152	58	530615	20
	sweet chestnut	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	1209	100	0	.	0	.	0	.	1209	100	13771	43	16190	38
	other broadleaves	185012	23	24667	34	54391	57	29713	33	112710	40	54373	36	84134	25	41862	25	114688	25	31316	32	26101	49	222213	43	144927	19	48933	29	1175038	11
	species not assessed in all inventories	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	total	2756004	13	1224538	22	843392	20	947124	20	2638145	13	309556	28	607191	17	1320754	19	598306	29	127949	27	245071	32	768249	33	419417	16	734794	21	13540490	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	71558	23	21955	27	41200	28	8490	37	4433	44	35188	32	84412	26	4612	40	466841	12
	fir	41635	29	3492	51	3412	43	68555	26	82734	26	5709	34	33784	35	8358	30	8001	46	499	100	1010	71	3015	53	499	100	1512	74	262214	13
	pine	539	100	0	.	1406	74	473	100	0	.	0	.	0	.	0	.	490	100	0	.	0	.	6384	86	8427	70	0	.	17719	46
	larch	0	.	0	.	0	.	0	.	553	100	0	.	0	.	0	.	0	.	0	.	0	.	956	71	12128	38	458	100	14096	33
	Arolla pine	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	1977	50	4441	43	917	100	7335	32
	other conifers	0	.	0	.	0	.	469	100	942	71	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	1410	58
	beech	429561	14	265615	29	155757	31	135961	28	229779	17	34548	45	79210	39	113337	30	51081	36	14091	70	15755	30	4388	58	26405	44	28080	61	1583566	8
	maple	81532	29	80529	50	66931	51	45573	30	264533	23	34023	64	21898	34	43531	39	18043	26	4521	53	1469	74	4974	49	2026	71	5942	35	675524	13
	ash	40401	24	19771	35	29050	37	40155	29	125623	20	18148	48	38698	42	24598	36	12698	39	9788	57	7964	50	11983	37	14738	53	57350	46	450966	10
	oak	971	71	0	.	14649	87	2083	50	2382	53	0	.	588	100	0	.	0	.	0	.	0	.	7024	39	1512	58	1938	71	31146	43
	sweet chestnut	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	2605	44	2605	44
	other broadleaves	63863	20	21357	32	26698	27	17870	34	66592	22	27138	65	44772	24	17052	24	42094	33	10858	37	4254	42	32624	27	42962	32	27493	38	445628	9
	species not assessed in all inventories	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	total	696244	11	392720	27	317109	22	366133	18	833530	13	140268	29	290507	16	228831	20	173605	18	48247	32	34885	24	108513	17	197551	18	130907	25	3959051	5
DBH 0-3.9 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	13824	25	883	66	6454	44	8560	28	11525	20	11754	35	23635	16	10915	24	17339	23	2337	44	4109	53	15295	26	35760	24	4414	38	166804	8
	fir	13468	22	7632	98	1699	58	31988	29	21878	33	2069	38	8587	41	5861	37	1048	47	552	58	529	74	3107	44	180	100	2158	39	100755	15
	pine	194	100	0	.	169	100	176	100	0	.	0	.	0	.	0	.	0	.	529	100	0	.	2485	48	5135	42	844	81	9531	28
	larch	0	.	177	100	537	73	0	.	399	100	0	.	0	.	0	.	0	.	0	.	0	.	2385	59	6324	32	367	70	10189	25
	Arolla pine	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	896	53	1959	35	0	.	2855	29
	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	248480	14	132926	21	47587	50	66748	23	215754	16	22185	47	70880	31	63421	23	9808	33	31010	89	7557	30	2174	62	23086	47	11194	41	952810	8
	maple	34601	22	12236	25	5433	39	29007	39	89807	20	8116	30	15937	27	22467	35	5585	29	3836	63	520	58	3170	47	1810	67	1305	55	233832	11
	ash	5928	26	3360	40	2685	44	4782	41	14591	30	1539	50	19437	58	2719	60	2456	66	1339	63	2465	55	2692	44	3974	50	2406	36	70372	19
	oak	194	100	0	.	4610	65	1256	38	1076	53	0	.	177	100	0	.	0	.	0	.	0	.	2115	70	176	100	0	.	9605	36
	sweet chestnut	0	.	0	.	199	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	188	100	0	.	2791	32	3179	29
	other broadleaves	29630	22	6836	43	12507	43	11446	35	28345	23	17014	26	23270	22	11597	31	13294	26	5629	34	3518	37	14611	27	10446	32	10670	24	198813	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	346498	11	164050	19	82079	32	154162	16	384228	11	62678	23	161922	17	116980	17	49529	16	45232	62	18699	27	49119	16	88850	17	36334	16	1760357	5
DBH 4-7.9 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	6332	21	691	51	1783	38	4403	25	5100	22	6463	27	9558	15	5506	25	7976	21	2235	29	2855	45	7272	19	15892	21	4478	22	80545	7
	fir	7252	15	1109	82	1222	39	6346	21	2722	38	1041	32	3985	24	2630	38	342	53	474	47	61	100	1574	43	134	71	1214	45	30106	9
	pine	76	100	0	.	0	.	0	.	156	70	0	.	138	100	0	.	0	.	0	.	0	.	1524	39	3111	46	322	100	5327	30
	larch	0	.	0	.	66	100	0	.	378	84	0	.	0	.	0	.	69	100	0	.	0	.	1263	32	1543	31	989	41	4307	19
	Arolla pine	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	702	40	1177	47	64	100	1943	32
	other conifers	0	.	0	.	156	100	69	100	222	58	0	.	0	.	0	.	0	.	0	.	0	0	0	0	0	0	0	0	446	47
	beech	14225	15	7119	25	1319	32	6645	22	13195	18	799	38	5386	21	4447	25	1478	29	851	53	1859	40	213	58	1180	40	4174	36	62889	7
	maple	5045	19	1885	31	589	46	1086	32	5529	22	797	38	1153	39	1093	31	1740	37	353	66	207	74	771	35	484	43	517	43	21248	9
	ash	856	43	580	50	421	47	1311	56	2146	32	349	100	1042	59	314	50	539	39	0	.	337	53	563	66	144	71	668	40	9269	15
	oak	0	0	0	.	156	70	78	100	291	50	0	.	0	.	0	.	0	.	0	.	0	.	278	61	0	.	215	74	1018	30
	sweet chestnut	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	676	36	676	36
	other broadleaves	4169	20	1751	29	1551	30	2732	26	3933	19	3314	30	2572	23	2264	32	3151	24	1787	39	489	51	5170	35	2286	51	7174	21	42344	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	37955	9	13135	19	7262	17	22669	13	33671	11	12763	18	23833	11	16255	15	15294	16	5700	25	5808	29	19329	15	25951	15	20493	13	260118	4
DBH 8-11.9 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	2042	22	825	42	958	39	3921	24	2449	24	2535	27	4183	18	2367	24	3558	22	1403	36	1756	35	3358	19	9834	16	2654	25	41842	6
	fir	4903	18	347	66	691	47	1905	29	1032	40	216	58	2986	23	1640	39	285	62	408	41	208	58	856	42	143	71	570	50	16189	10
	pine	0	.	0	.	0	.	78	100	156	100	0	.	0	.	0	.	0	.	217	100	0	.	975	39	1313	40	451	100	3189	26
	larch	68	100	0	.	78	100	78	100	156	100	174	100	0	.	60	100	0	.	0	.	0	.	1280	27	911	37	689	50	3492	19
	Arolla pine	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	140	100	971	37	0	.	1111	35
	other conifers	69	100	0	.	0	.	78	100	0	0	0	.	0	0	0	.	0	.	0	.	0	0	0	.	0	0	0	.	147	71
	beech	5429	17	3143	22	1118	34	2925	24	4528	18	296	50	2508	23	1233	30	549	49	416	48	903	51	0	0	219	74	3315	24	26582	7
	maple	2132	23	1074	33	725	49	413	41	1448	25	60	100	590	41	379	52	691	47	69	100	344	53	568	35	510	88	362	52	9367	12
	ash	363	45	203	74	137	100	415	57	333	53	496	89	60	100	71	100	624	71	70	100	69	100	354	53	138	100	370	45	3702	22
	oak	956	79	76	100	78	100	78	100	611	56	0	.	0	.	0	.	0	.	0	.	0	.	557	50	0	.	72	100	2428	37
	sweet chestnut	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	365	45	365	45
	other broadleaves	1820	24	482	62	784	39	1260	28	2257	20	971	40	1620	33	836	40	562	43	416	48	482	43	2517	22	1520	54	4149	20	19674	9
	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	17782	10	6149	18	4570	21	11149	15	12968	11	4749	20	11946	12	6586	16	6270	18	2999	26	3761	23	10604	12	15560	13	12997	11	128090	4
total	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	154137	23	15263	43	43730	49	170500	38	153689	28	53752	27	217794	17	117556	26	141206	20	24351	29	20192	32	117361	20	218934	19	22024	29	1470489	8
	fir	227686	16	36069	39	50879	32	251698	17	305579	18	61866	30	111462	20	169972	31	33151	37	4502	44	5671	52	17222	47	2166	61	11168	34	1289090	8
	pine	2306	100	0	.	3112	60	726	70	311	79	0	.	138	100	0	.	490	100	746	77	0	.	12728	60	23453	38	1618	89	45628	27
	larch	68	100	177	100	681	67	78	100	1485	96	174	100	0	.	60	100	69	100	0	.	0	.	5883	36	24986	26	3777	40	37439	19
	Arolla pine	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	10645	66	8548	31	3529	77	22722	35
	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	184	100	22662	34
	beech	1458678	13	696029	20	452335	36	386181	19	918521	13	84232	42	276895	32	520354	28	288403	50	65717	58	130760	48	28297	49	102965	31	178510	34	5587877	7
	maple	912900	17	641284	32	334398	34	328783	27	1536961	19	146731	50	157238	30	476560	24	120707	32	27827	34	29743	44	31837	31	47416	39	49629	25	4842014	9
	ash	633127	20	275982	23	169242	27	280959	39	680076	16	80449	44	171701	27	321242	25	83979	30	56977	46	87014	32	400208	57	113822	42	496083	31	3850862	9
	oak	172631	47	80696	54	103549	36	14412	44	84699	40	0	.	3801	59	8648	47	0	.	0	.	0	.	54310	29	1688	53	50377	56	574811	19
	sweet chestnut	0	.	0	.	199	100	0	.	0	.	0	.	0	.	0	.	1209	100	0	.	0	.	188	100	1209	100	20209	30	23015	28
	other broadleaves	284494	18	55093	26	95932	38	63020	27	213836	23	102809	36	156368	18	73611	19	173790	24	50007	28	34844	38	277135	35	202141	17	98418	23	1881497	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	3854483	10	1800592	19	1254412	19	1501238	16	3902542	11	530013	24	1095398	13	1689407	16	843004	23	230127	26	308224	26	955814	27	747328	13	935524	19	19648107	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. 1196517. Birmensdorf, Swiss Federal Research Institute WSL

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