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
total number of stems with two most important forms of damages
altitude (in 200 m classes) · cause of damage to trees (10 classes)
regional demarcation: protection forest region
unit: 1000 n
evaluation area: accessible forest without shrub forest
grid: 1.4 km grid, subgrids 1-5
state 2018/26
		protection forest region
		Jura + Plateau		Northwestern Alps		Northeastern Alps		Southwestern Alps		Southeastern Alps		Southern Alps		Switzerland
altitude (in 200 m classes)	cause of damage to trees (10 classes)	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	.
	no visible damage	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	fire	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	rockfall	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	various	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	indeterminable	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	wood harvest	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	other human activity	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	weather	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	lying living trees	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	dead trees	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	total	.	.	.	.	.	.	.	.	.	.	.	.	.	.
>1800 m	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	no visible damage	0	.	1335	47	325	81	5873	16	11610	12	3932	17	23075	8
	fire	0	.	0	.	0	.	0	.	0	.	7	100	7	100
	rockfall	0	.	0	.	0	.	333	26	154	43	343	53	830	26
	various	0	.	50	54	28	100	243	36	630	25	215	26	1166	16
	indeterminable	0	.	418	39	115	71	2149	18	4627	13	1481	18	8789	9
	wood harvest	0	.	0	.	0	.	79	53	20	76	0	.	100	45
	other human activity	0	.	23	72	0	.	293	46	84	54	63	69	462	33
	weather	0	.	0	.	18	100	427	26	290	26	615	39	1350	20
	lying living trees	0	.	0	.	0	.	140	56	452	39	93	49	684	29
	dead trees	0	.	459	56	18	100	1827	21	2994	16	876	29	6175	11
	total	.	.	.	.	.	.	.	.	.	.	.	.	.	.
1601-1800 m	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	no visible damage	0	.	6341	21	1607	39	6706	18	8661	14	4947	17	28262	8
	fire	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	rockfall	0	.	339	35	0	.	163	36	325	35	206	52	1033	20
	various	0	.	392	40	243	57	196	30	424	29	355	33	1611	17
	indeterminable	0	.	1996	20	581	40	2402	17	2797	15	1145	21	8921	9
	wood harvest	0	.	55	100	0	.	7	100	41	46	27	100	130	50
	other human activity	0	.	80	54	95	93	227	52	222	40	43	61	667	27
	weather	0	.	239	34	24	77	453	42	328	32	293	23	1337	18
	lying living trees	0	.	136	61	22	100	68	48	53	74	16	100	294	34
	dead trees	0	.	1940	26	316	47	2251	25	1410	18	659	24	6577	12
	total	.	.	.	.	.	.	.	.	.	.	.	.	.	.
1401-1600 m	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	no visible damage	1065	29	10248	14	4467	19	6067	17	9563	14	7423	17	38834	7
	fire	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	rockfall	13	100	824	38	82	47	388	41	519	44	402	34	2227	20
	various	138	47	300	29	266	47	231	31	192	42	495	24	1623	14
	indeterminable	246	31	3521	13	1119	23	1818	18	2769	15	1556	18	11030	7
	wood harvest	8	100	105	48	44	85	37	56	131	42	18	100	342	26
	other human activity	0	.	338	36	86	84	673	75	199	37	42	71	1340	40
	weather	26	78	333	25	171	51	337	30	279	29	419	25	1564	13
	lying living trees	0	.	55	58	162	58	198	60	88	53	102	52	605	28
	dead trees	185	63	3285	16	1272	31	1568	20	2385	23	1486	20	10182	9
	total	.	.	.	.	.	.	.	.	.	.	.	.	.	.
1201-1400 m	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	no visible damage	5881	16	11017	12	6589	14	5784	19	3860	21	5148	18	38280	6
	fire	0	.	0	.	0	.	0	.	0	.	33	100	33	100
	rockfall	150	87	940	29	1128	33	459	40	265	54	699	27	3641	15
	various	305	30	502	28	669	26	743	47	114	47	445	29	2779	16
	indeterminable	1012	19	2969	13	1761	16	931	23	1593	22	1475	18	9741	7
	wood harvest	111	44	158	42	191	46	0	.	109	45	60	50	629	21
	other human activity	83	41	311	44	143	47	18	100	159	49	26	76	739	24
	weather	260	44	366	26	274	40	101	51	186	47	340	28	1526	15
	lying living trees	0	.	36	71	254	55	78	47	0	.	125	39	493	31
	dead trees	857	25	3018	17	2310	20	1331	22	1237	24	1133	24	9886	9
	total	.	.	.	.	.	.	.	.	.	.	.	.	.	.
1001-1200 m	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	no visible damage	13216	9	13177	11	7635	15	4041	19	2940	24	6511	17	47520	6
	fire	0	.	0	.	0	.	0	.	6	100	72	91	78	84
	rockfall	398	36	1229	28	825	33	328	52	447	44	854	27	4080	14
	various	486	26	410	27	752	29	218	37	281	48	440	40	2587	14
	indeterminable	1753	13	2354	15	2024	15	886	26	1285	28	1669	19	9972	7
	wood harvest	765	19	417	28	431	30	7	100	33	81	7	100	1660	14
	other human activity	191	37	217	50	314	39	15	71	55	58	25	100	817	22
	weather	200	36	606	25	222	32	144	35	172	63	377	26	1721	14
	lying living trees	0	.	70	63	131	64	139	66	18	100	169	60	527	32
	dead trees	1581	17	2567	15	2141	21	1096	26	694	28	1217	25	9295	8
	total	.	.	.	.	.	.	.	.	.	.	.	.	.	.
801-1000 m	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	no visible damage	18823	9	12978	12	9472	13	2952	25	2055	27	6609	23	52887	6
	fire	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	rockfall	1107	33	427	50	1353	28	362	64	88	60	592	30	3928	16
	various	483	23	672	22	537	22	84	53	116	44	502	40	2394	13
	indeterminable	3200	12	1888	16	1855	16	844	27	838	28	1934	23	10559	7
	wood harvest	973	21	523	31	487	29	33	100	87	48	0	0	2103	14
	other human activity	361	33	300	43	224	35	7	100	50	74	90	43	1033	19
	weather	440	24	301	35	313	26	40	71	227	45	549	54	1870	19
	lying living trees	0	.	102	51	40	62	18	100	18	100	204	58	382	35
	dead trees	2285	14	2376	17	2288	18	765	30	452	28	1945	24	10111	8
	total	.	.	.	.	.	.	.	.	.	.	.	.	.	.
601-800 m	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	no visible damage	35659	7	8321	13	5262	19	1196	46	2132	25	4541	19	57111	5
	fire	0	.	0	.	0	.	0	.	0	.	424	69	424	69
	rockfall	675	35	613	44	336	45	147	62	147	71	391	30	2310	18
	various	1459	17	783	38	473	34	76	81	171	31	1238	40	4200	16
	indeterminable	5067	10	1476	17	1338	21	300	46	570	31	2052	20	10803	7
	wood harvest	2181	12	434	30	98	41	0	.	33	100	90	100	2836	11
	other human activity	521	27	85	45	26	75	0	.	14	71	28	77	674	22
	weather	718	17	129	39	111	45	42	61	38	83	774	43	1812	20
	lying living trees	85	53	36	71	75	49	36	71	0	.	98	44	330	25
	dead trees	4795	10	1339	22	1181	23	477	37	413	35	2317	21	10522	8
	total	.	.	.	.	.	.	.	.	.	.	.	.	.	.
=600 m	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	no visible damage	46495	5	1347	42	2070	28	1289	36	35	100	6550	18	57786	5
	fire	0	.	0	.	0	.	0	.	0	.	126	100	126	100
	rockfall	299	71	7	100	413	74	48	73	0	.	479	34	1247	33
	various	1875	13	74	72	122	68	112	59	0	.	831	34	3015	13
	indeterminable	6940	7	232	60	477	34	203	47	0	.	3027	18	10879	7
	wood harvest	2887	11	71	78	58	58	18	100	0	.	0	.	3034	11
	other human activity	801	25	0	0	52	55	75	100	0	.	192	41	1120	20
	weather	1096	15	44	72	89	58	36	71	0	.	430	28	1695	12
	lying living trees	249	26	15	100	21	74	18	100	0	.	323	41	627	24
	dead trees	6000	9	212	42	492	31	431	42	0	.	3335	17	10471	8
	total	.	.	.	.	.	.	.	.	.	.	.	.	.	.
total	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	no visible damage	121140	2	64765	5	37426	6	33908	7	40856	6	45661	5	343756	2
	fire	0	.	0	.	0	.	0	.	6	100	662	50	669	49
	rockfall	2642	19	4380	15	4137	17	2226	18	1945	19	3967	11	19297	6
	various	4746	8	3183	13	3092	13	1903	20	1929	14	4520	14	19374	5
	indeterminable	18218	4	14853	6	9272	7	9531	8	14480	7	14339	6	80692	2
	wood harvest	6925	7	1762	15	1309	17	183	34	454	21	202	50	10834	5
	other human activity	1956	14	1354	19	940	21	1308	42	783	20	510	22	6852	10
	weather	2739	9	2019	12	1221	16	1581	16	1519	15	3797	14	12875	6
	lying living trees	334	24	448	26	705	28	696	26	629	30	1132	20	3943	11
	dead trees	15703	5	15197	7	10019	9	9747	9	9585	9	12967	7	73219	3
	total	.	.	.	.	.	.	.	.	.	.	.	.	.	.

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. 1346982. Birmensdorf, Swiss Federal Research Institute WSL

back