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.

NFI2
number of stems
altitude (in 200 m classes) · number of cases of damage
regional demarcation: economic region
unit: n/ha
evaluation area: accessible forest without shrub forest
grid: 1.4-km grid
state 1993/95
		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
altitude (in 200 m classes)	number of cases of damage	n/ha	±%	n/ha	±%	n/ha	±%	n/ha	±%	n/ha	±%	n/ha	±%	n/ha	±%	n/ha	±%	n/ha	±%	n/ha	±%	n/ha	±%	n/ha	±%	n/ha	±%	n/ha	±%	n/ha	±%
n/a	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	no visible damage	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	one visible damage	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	two or more visible damages	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	dead or lying tree	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	.
>1800 m	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	no visible damage	0	.	0	.	0	.	0	.	0	.	280	21	372	34	0	.	259	29	283	3	230	0	234	9	275	6	183	13	250	5
	one visible damage	0	.	0	.	0	.	0	.	0	.	134	47	55	33	0	.	44	28	23	68	50	0	76	10	70	7	43	16	67	6
	two or more visible damages	0	.	0	.	0	.	0	.	0	.	11	75	47	55	0	.	19	41	57	68	0	.	22	16	10	19	15	21	16	10
	dead or lying tree	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	28	68	0	.	2	56	8	46	5	61	5	34
	total	0	.	0	.	0	.	0	.	0	.	426	31	474	29	0	.	322	25	391	21	280	0	334	7	363	5	246	11	337	4
1601-1800 m	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	no visible damage	0	.	0	.	0	.	0	.	0	.	306	29	387	22	583	8	238	17	322	34	224	25	318	10	277	7	234	10	282	5
	one visible damage	0	.	0	.	0	.	0	.	0	.	88	29	72	18	70	0	65	23	71	37	77	29	114	12	63	9	53	14	74	6
	two or more visible damages	0	.	0	.	0	.	0	.	0	.	24	56	9	54	34	31	36	39	30	52	12	41	30	15	21	17	14	21	22	10
	dead or lying tree	0	.	0	.	0	.	0	.	0	.	0	.	3	98	52	68	0	.	0	.	0	.	3	67	1	46	2	57	2	32
	total	0	.	0	.	0	.	0	.	0	.	419	28	471	19	739	3	339	14	423	22	314	23	465	9	362	6	303	9	381	4
1401-1600 m	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	no visible damage	177	17	0	.	221	29	0	.	0	.	349	15	357	13	249	19	248	13	196	26	172	26	241	9	283	10	283	8	270	4
	one visible damage	50	22	0	.	48	27	0	.	0	.	104	21	70	14	76	35	79	12	63	21	48	23	77	11	62	9	64	12	70	5
	two or more visible damages	12	46	0	.	11	63	0	.	0	.	17	34	14	28	14	38	36	21	24	32	17	25	28	15	17	16	17	21	21	8
	dead or lying tree	0	.	0	.	0	.	0	.	0	.	2	99	3	89	0	.	2	74	0	.	0	.	6	34	1	57	4	45	3	23
	total	239	13	0	.	281	27	0	.	0	.	472	14	444	12	339	21	365	10	282	20	237	22	353	7	363	8	367	7	364	4
1201-1400 m	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	no visible damage	258	7	0	.	324	26	410	0	0	.	457	11	300	9	252	10	356	10	323	17	320	17	350	10	279	9	344	9	317	3
	one visible damage	61	12	0	.	22	88	170	0	0	.	127	18	86	13	84	13	84	13	95	19	97	17	100	12	84	13	76	12	86	5
	two or more visible damages	17	19	0	.	16	54	0	.	0	.	47	32	39	19	29	25	39	38	37	29	38	44	31	22	24	19	20	17	30	9
	dead or lying tree	0	.	0	.	0	.	0	.	0	.	0	.	2	72	3	61	0	.	7	59	6	69	4	45	0	.	0	99	2	26
	total	337	6	0	.	362	25	580	0	0	.	632	10	427	7	368	9	479	8	462	16	460	13	485	8	387	8	440	8	433	3
1001-1200 m	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	no visible damage	368	5	190	0	197	19	186	47	297	8	430	11	315	7	381	8	306	13	352	14	384	24	288	11	307	9	352	9	347	3
	one visible damage	77	7	50	0	78	20	76	34	84	55	94	15	101	9	95	11	87	16	113	19	107	22	98	16	102	19	69	10	89	4
	two or more visible damages	19	13	50	0	10	68	0	.	14	64	29	20	40	15	26	17	30	28	30	24	46	23	33	25	39	22	27	17	29	6
	dead or lying tree	1	61	0	.	0	.	0	.	0	.	0	.	1	76	1	100	3	56	8	76	2	98	2	70	3	56	5	44	2	23
	total	465	4	290	0	285	16	261	35	395	15	554	9	457	6	503	8	428	10	503	12	539	19	421	10	451	10	452	7	466	2
801-1000 m	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	no visible damage	329	6	398	11	381	13	358	18	350	15	441	13	347	6	447	8	363	21	467	15	336	18	358	11	271	13	346	9	362	3
	one visible damage	95	7	82	24	63	18	76	18	115	19	88	16	102	11	96	13	104	17	169	20	114	16	105	18	76	14	89	14	96	4
	two or more visible damages	41	14	42	25	7	42	24	27	21	31	22	26	38	16	27	19	27	31	45	36	93	19	41	19	28	29	39	16	36	6
	dead or lying tree	1	70	0	.	0	.	0	.	0	.	0	.	2	50	0	100	2	99	0	.	1	99	1	99	7	52	2	73	1	27
	total	466	5	522	11	451	12	457	14	486	13	551	11	489	6	570	7	495	17	681	12	544	13	505	9	382	10	476	8	496	2
601-800 m	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	no visible damage	353	5	345	9	364	7	344	6	382	6	459	16	350	8	421	8	496	15	164	26	372	25	266	15	321	14	329	9	358	2
	one visible damage	89	7	79	17	73	10	62	9	57	8	41	47	84	12	64	12	88	41	115	33	120	24	95	19	68	16	103	14	77	4
	two or more visible damages	26	13	23	33	18	18	14	18	13	18	18	47	31	18	19	30	9	61	58	31	52	26	41	23	24	53	77	15	27	6
	dead or lying tree	0	.	0	.	1	70	0	100	1	49	0	.	0	.	1	99	0	.	0	.	3	97	6	60	7	90	1	99	1	30
	total	468	4	446	8	456	6	420	5	453	6	518	14	465	7	505	7	593	14	337	21	547	21	408	11	421	11	509	8	463	2
=600 m	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	no visible damage	352	7	346	6	450	7	381	6	347	4	0	.	466	21	542	12	472	27	431	20	198	45	336	21	374	20	364	8	370	2
	one visible damage	79	11	55	9	65	16	62	7	48	7	0	.	49	28	129	32	78	34	191	22	27	48	119	37	23	65	103	10	65	4
	two or more visible damages	28	21	11	25	10	45	21	16	12	13	0	.	22	40	22	62	15	59	38	33	0	.	17	46	0	.	59	14	20	7
	dead or lying tree	0	100	1	60	5	78	0	76	0	100	0	.	0	.	0	.	0	.	6	94	0	.	0	.	0	.	2	84	1	39
	total	459	6	412	5	530	6	465	5	407	4	0	.	538	19	693	13	564	25	666	10	224	45	472	20	397	22	528	7	455	2
total	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	no visible damage	334	3	349	5	386	5	365	4	356	3	416	6	341	4	385	4	312	6	322	8	303	9	288	4	283	3	314	3	333	1
	one visible damage	81	4	63	8	67	8	64	5	53	5	101	9	89	5	88	7	81	7	111	9	93	9	93	5	71	4	77	5	78	2
	two or more visible damages	26	7	17	17	13	16	18	12	12	10	29	16	33	8	24	11	31	14	37	13	46	13	30	7	20	8	35	7	26	3
	dead or lying tree	0	42	1	61	2	65	0	61	1	52	0	100	2	35	1	42	1	43	4	41	2	46	3	21	4	29	2	23	2	11
	total	442	2	429	4	468	4	447	4	422	3	547	5	464	3	499	4	426	5	473	6	444	7	414	3	377	3	428	3	438	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. 1198834. Birmensdorf, Swiss Federal Research Institute WSL

back