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.

NFI1
total number of stems NFI1
diameter at breast height (10 classes) · main tree species
regional demarcation: protection forest region
unit: 1000 n
evaluation area: accessible forest without shrub forest NFI1-NFI5
grid: 1.4 km grid, subgrids 1-5
state 1983/85
		protection forest region
		Jura + Plateau		Northwestern Alps		Northeastern Alps		Southwestern Alps		Southeastern Alps		Southern Alps		Switzerland
diameter at breast height (10 classes)	main tree species	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	.
	spruce	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	fir	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	pine	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	larch	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	Arolla pine	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	other conifers	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	beech	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	maple	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	ash	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	oak	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	sweet chestnut	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	other broadleaves	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	indeterminable	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	total	0	.	0	.	0	.	0	.	0	.	0	.	0	.
12-20 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	24059	8	19121	9	10294	12	8080	13	11627	10	2871	15	76051	4
	fir	13221	8	6148	10	2838	15	572	36	396	29	611	34	23786	6
	pine	1352	29	605	55	199	57	4036	22	2503	24	101	69	8796	13
	larch	282	35	55	74	90	72	2578	18	935	23	1783	20	5723	11
	Arolla pine	0	.	0	.	0	.	389	34	844	24	0	.	1234	19
	other conifers	931	29	17	100	223	36	87	100	70	78	0	.	1327	23
	beech	24668	5	7705	11	5412	13	1200	34	1068	26	6572	15	46625	4
	maple	4410	10	2447	15	1591	19	490	39	167	57	282	32	9387	7
	ash	4535	12	2305	22	1882	23	342	37	420	67	914	27	10399	9
	oak	3477	22	398	36	61	58	426	36	31	100	1291	38	5685	17
	sweet chestnut	0	.	0	.	0	.	93	72	0	.	8737	15	8830	15
	other broadleaves	7869	11	3514	14	3311	22	2339	19	2109	24	9074	11	28217	6
	indeterminable	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	total	84802	4	42316	6	25901	8	20632	9	20171	8	32237	6	226060	2
21-30 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	13430	7	12224	8	8293	11	5213	12	8312	10	2592	17	50063	4
	fir	8249	8	3473	11	1979	16	310	42	158	40	166	48	14335	6
	pine	1367	20	277	49	287	44	1884	20	1466	20	137	55	5417	11
	larch	311	37	54	58	71	79	1941	18	1159	18	1177	21	4714	10
	Arolla pine	0	.	0	.	0	.	378	29	684	29	0	.	1062	21
	other conifers	152	37	0	.	15	100	0	.	0	.	0	.	167	35
	beech	15727	5	4007	11	3636	13	472	40	562	31	2648	16	27052	4
	maple	3014	10	1222	17	1471	16	75	50	128	48	56	58	5965	7
	ash	3173	11	760	23	1208	21	140	49	184	64	78	50	5542	9
	oak	2285	12	80	50	74	77	94	64	0	.	470	34	3004	11
	sweet chestnut	0	.	0	.	0	.	19	100	15	100	2681	18	2715	18
	other broadleaves	2870	12	529	24	741	23	314	32	351	52	2378	16	7184	8
	indeterminable	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	total	50577	3	22625	6	17775	7	10840	9	13020	8	12383	7	127221	2
31-40 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	11651	6	9089	7	5208	10	3006	12	5288	9	1687	16	35929	3
	fir	5698	7	2202	12	1416	14	194	47	144	31	230	34	9884	5
	pine	2199	13	119	41	92	52	503	21	868	21	111	67	3891	10
	larch	255	28	58	53	0	.	1269	15	1159	17	741	21	3482	9
	Arolla pine	0	.	8	100	0	.	212	38	472	25	0	.	693	20
	other conifers	100	50	0	.	0	.	17	100	0	.	0	.	117	45
	beech	8710	6	2160	13	1914	15	96	56	250	35	753	18	13883	5
	maple	1014	13	400	27	560	21	26	100	16	72	26	77	2041	10
	ash	1555	12	300	27	269	27	33	100	15	100	41	84	2214	10
	oak	1000	14	14	100	17	72	0	.	36	72	255	37	1321	13
	sweet chestnut	0	.	0	.	0	.	42	70	6	100	573	21	621	20
	other broadleaves	1064	15	252	32	160	30	102	45	118	55	537	25	2233	11
	indeterminable	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	total	33245	3	14602	6	9635	7	5501	9	8372	7	4953	8	76309	2
41-50 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	7507	5	5590	7	3373	9	1594	12	3002	9	1126	14	22191	3
	fir	2856	7	1616	10	838	15	151	33	118	40	196	31	5774	5
	pine	1308	13	196	47	70	58	201	35	360	24	7	100	2141	10
	larch	145	28	35	45	34	54	842	14	707	15	454	16	2218	8
	Arolla pine	0	.	0	.	0	.	63	47	176	29	0	.	240	24
	other conifers	129	54	0	.	0	.	0	.	0	.	0	.	129	54
	beech	4001	6	987	16	783	15	43	59	179	33	310	21	6304	5
	maple	281	18	114	28	120	29	0	.	21	58	0	.	537	13
	ash	504	15	61	45	125	29	0	.	0	.	18	72	708	12
	oak	507	17	0	.	6	100	0	.	20	76	38	51	571	16
	sweet chestnut	0	.	0	.	0	.	7	100	6	100	317	22	331	21
	other broadleaves	200	25	67	41	47	38	37	53	7	100	66	44	424	16
	indeterminable	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	total	17438	3	8665	5	5397	7	2938	9	4597	7	2533	8	41568	2
51-60 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	3154	7	2338	8	1665	11	730	14	1407	11	537	16	9831	4
	fir	1024	11	747	14	364	18	65	46	57	43	30	49	2286	7
	pine	316	19	35	76	0	.	35	45	158	33	14	71	558	15
	larch	62	33	79	37	53	53	438	17	410	18	265	21	1306	10
	Arolla pine	0	.	0	.	0	.	14	71	86	33	0	.	100	30
	other conifers	22	73	0	.	0	.	0	.	0	.	0	.	22	73
	beech	1241	10	504	20	255	24	14	100	58	52	152	30	2223	8
	maple	93	33	20	58	18	74	0	.	6	100	0	.	137	26
	ash	154	23	22	58	7	100	0	.	12	100	0	.	196	21
	oak	234	20	0	.	0	.	0	.	0	.	8	100	242	20
	sweet chestnut	0	.	0	.	0	.	7	100	0	.	116	28	123	27
	other broadleaves	90	34	38	52	15	100	23	74	0	.	23	57	188	23
	indeterminable	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	total	6388	4	3784	7	2376	9	1326	11	2195	9	1144	10	17212	3
61-70 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	774	11	649	13	608	16	184	28	362	17	240	26	2817	6
	fir	271	16	264	21	41	41	13	71	12	100	24	58	624	12
	pine	62	40	11	100	7	100	0	.	28	50	0	.	108	29
	larch	14	71	7	100	24	58	208	25	162	25	92	33	507	15
	Arolla pine	0	.	0	.	0	.	7	100	29	62	0	.	36	53
	other conifers	7	100	7	100	0	.	0	.	0	.	0	.	14	71
	beech	386	17	93	31	35	50	7	100	33	52	52	38	606	13
	maple	29	50	0	.	0	.	0	.	0	.	0	.	29	50
	ash	42	47	0	.	7	100	0	.	0	.	0	.	49	43
	oak	36	45	0	.	12	100	0	.	0	.	0	.	48	42
	sweet chestnut	0	.	0	.	0	.	0	.	0	.	53	43	53	43
	other broadleaves	8	100	6	100	10	100	8	100	0	.	7	100	38	45
	indeterminable	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	total	1627	8	1037	10	744	15	427	18	626	13	467	16	4929	5
71-80 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	228	19	161	22	261	25	71	34	167	21	91	38	978	10
	fir	154	24	120	27	34	54	0	.	15	70	30	60	352	16
	pine	7	100	0	.	0	.	0	.	7	100	0	.	14	71
	larch	14	71	0	.	0	.	121	31	48	38	36	45	219	21
	Arolla pine	0	.	0	.	0	.	35	53	15	71	0	.	50	43
	other conifers	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	beech	60	36	25	58	7	100	7	100	0	.	7	100	107	27
	maple	0	.	6	100	17	73	0	.	0	.	0	.	23	60
	ash	24	59	0	.	0	.	0	.	0	.	0	.	24	59
	oak	54	38	0	.	6	100	0	.	0	.	0	.	60	36
	sweet chestnut	0	.	0	.	0	.	7	100	0	.	93	50	100	47
	other broadleaves	8	100	0	.	0	.	0	.	0	.	0	.	8	100
	indeterminable	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	total	547	12	312	17	325	21	242	21	252	17	257	24	1934	7
81-90 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	59	35	30	50	73	35	15	71	35	45	14	71	225	19
	fir	7	100	52	38	9	100	7	100	0	.	18	72	93	29
	pine	8	100	0	.	0	.	0	.	0	.	0	.	8	100
	larch	0	.	0	.	0	.	15	71	21	58	0	.	36	45
	Arolla pine	0	.	0	.	0	.	7	100	0	.	0	.	7	100
	other conifers	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	beech	43	41	0	.	7	100	0	.	12	70	0	.	63	33
	maple	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	ash	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	oak	36	45	0	.	0	.	0	.	0	.	0	.	36	45
	sweet chestnut	0	.	0	.	0	.	0	.	0	.	33	50	33	50
	other broadleaves	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	indeterminable	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	total	153	24	82	30	89	31	43	41	68	32	65	36	500	13
91-100 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	28	50	6	100	36	45	0	.	23	58	0	.	93	28
	fir	14	70	0	.	0	.	0	.	0	.	0	.	14	70
	pine	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	larch	0	.	0	.	0	.	14	71	0	.	7	100	21	58
	Arolla pine	0	.	0	.	0	.	7	100	0	.	0	.	7	100
	other conifers	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	beech	14	71	0	.	0	.	0	.	0	.	0	.	14	71
	maple	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	ash	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	oak	7	100	0	.	0	.	0	.	0	.	0	.	7	100
	sweet chestnut	0	.	0	.	0	.	0	.	0	.	35	51	35	51
	other broadleaves	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	indeterminable	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	total	63	33	6	100	36	45	21	58	23	58	42	46	191	20
>100 cm	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	0	.	16	71	0	.	14	71	0	.	7	100	38	45
	fir	7	100	0	.	0	.	0	.	0	.	11	100	18	73
	pine	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	larch	0	.	0	.	0	.	0	.	7	100	7	100	14	71
	Arolla pine	0	.	0	.	0	.	7	100	7	100	0	.	14	71
	other conifers	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	beech	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	maple	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	ash	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	oak	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	sweet chestnut	0	.	0	.	0	.	0	.	0	.	52	49	52	49
	other broadleaves	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	indeterminable	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	total	7	100	16	71	0	.	21	58	14	71	78	38	137	26
total	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	60888	5	49224	6	29809	8	18907	10	30223	8	9165	12	198215	3
	fir	31500	6	14623	8	7518	11	1311	29	900	25	1314	27	57166	4
	pine	6618	11	1242	41	655	40	6659	19	5390	17	369	52	20932	9
	larch	1083	21	289	34	272	45	7427	12	4609	12	4561	14	18241	7
	Arolla pine	0	.	8	100	0	.	1121	23	2313	20	0	.	3442	15
	other conifers	1340	24	24	77	238	37	104	85	70	78	0	.	1777	20
	beech	54851	4	15480	9	12049	11	1840	31	2163	23	10494	14	96878	3
	maple	8840	7	4209	12	3776	14	591	37	338	36	365	32	18119	6
	ash	9986	9	3448	18	3498	18	515	32	632	62	1052	25	19132	7
	oak	7635	13	492	33	177	44	520	39	87	75	2063	27	10974	11
	sweet chestnut	0	.	0	.	0	.	175	61	28	100	12690	13	12893	13
	other broadleaves	12108	9	4405	13	4285	19	2823	19	2585	23	12085	10	38291	5
	indeterminable	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	total	194847	2	93446	4	62277	6	41993	7	49338	6	54159	5	496061	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. 1344337. Birmensdorf, Swiss Federal Research Institute WSL

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