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
conifers and broadleaves · diameter at breast height (10 classes)
regional demarcation: canton
unit: n/ha
evaluation area: accessible forest without shrub forest NFI4/NFI5
grid: 1.4 km grid, subgrids 1-5
state 2018/26
		canton
		AG		AI		AR		BE		BL/BS		FR		GE		GL		GR		JU		LU		NE		NW		OW		SG		SH		SO		SZ		TG		TI		UR		VD		VS		ZG		ZH		Switzerland
conifers and broadleaves	diameter at breast height (10 classes)	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/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	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	12-20 cm	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	.
	21-30 cm	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	.
	31-40 cm	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	.
	41-50 cm	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	.
	51-60 cm	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	.
	61-70 cm	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	.
	71-80 cm	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	.
	81-90 cm	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	.
	91-100 cm	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	.
	>100 cm	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	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	.
conifers	n/a	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	.
	12-20 cm	41	19	48	26	75	34	92	7	51	30	86	18	34	74	62	29	127	6	69	14	132	13	80	19	108	59	171	20	70	17	36	42	60	30	79	20	62	21	54	14	130	16	84	12	115	8	50	42	49	23	89	3
	21-30 cm	29	23	68	26	59	35	54	7	20	29	59	18	0	.	34	29	80	6	36	19	68	12	59	14	91	34	104	20	45	14	30	31	28	23	49	19	51	21	35	13	95	14	48	11	82	9	62	27	32	21	56	3
	31-40 cm	13	26	100	17	60	23	36	7	13	28	46	16	18	93	21	28	51	6	22	22	38	11	33	19	59	34	65	21	32	14	27	31	21	24	39	18	26	31	21	13	58	17	33	10	50	8	46	25	23	17	36	3
	41-50 cm	9	22	64	15	36	24	27	6	9	28	30	13	5	93	26	21	34	5	22	18	26	11	26	13	31	31	31	19	20	13	15	25	12	18	29	15	16	18	13	13	36	21	23	9	30	8	30	32	20	13	25	2
	51-60 cm	6	20	51	19	38	25	17	7	7	34	19	14	0	.	17	20	20	6	15	18	21	12	20	13	9	43	16	22	17	11	7	29	6	24	21	15	6	27	9	16	16	21	13	10	18	8	18	37	9	16	15	3
	61-70 cm	3	30	20	25	9	43	8	9	3	40	6	18	0	.	8	33	8	9	7	25	9	18	9	21	13	37	5	35	11	16	5	36	2	47	9	24	4	28	3	15	7	25	8	14	7	12	3	97	5	21	7	4
	71-80 cm	2	30	4	52	3	46	4	11	2	58	3	29	0	.	7	36	3	12	3	40	4	23	4	22	4	46	6	36	6	19	2	59	1	57	4	28	2	54	2	24	3	44	3	19	4	17	3	66	2	29	3	5
	81-90 cm	1	61	1	97	0	.	1	21	0	99	1	42	0	.	2	42	2	19	0	70	1	44	2	38	0	.	1	76	2	29	0	.	0	70	1	50	1	52	1	35	0	99	1	35	1	26	2	96	1	37	1	8
	91-100 cm	0	100	0	.	0	.	0	33	0	.	0	100	0	.	2	48	1	28	0	100	0	.	0	100	0	.	0	.	0	70	0	.	0	99	0	99	1	70	0	58	0	.	0	50	1	31	0	.	0	.	0	14
	>100 cm	0	.	0	.	0	.	0	50	0	.	0	100	0	.	0	99	0	35	0	70	0	100	0	100	0	.	0	.	0	57	0	.	0	.	0	99	0	.	0	71	0	.	0	100	0	71	0	.	0	.	0	19
	total	104	14	357	15	281	19	239	4	106	19	250	12	57	61	180	20	325	4	175	10	299	8	235	10	315	34	397	14	203	9	123	21	131	17	231	10	169	15	138	10	346	12	213	7	308	6	213	23	141	13	234	2
broadleaves	n/a	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	.
	12-20 cm	93	12	9	69	49	29	71	8	136	17	72	16	87	47	59	21	38	15	85	16	62	14	71	17	128	25	57	28	77	14	106	22	116	18	75	19	80	17	181	7	78	26	97	11	69	11	33	39	86	12	83	3
	21-30 cm	42	14	10	70	47	29	37	8	68	19	53	14	48	55	42	24	20	15	45	17	29	16	33	15	103	37	31	32	55	14	55	26	62	14	45	23	42	16	101	7	53	24	45	11	26	14	24	52	45	14	44	3
	31-40 cm	21	16	15	43	34	27	21	8	46	17	30	17	26	54	22	26	8	17	36	16	22	16	13	28	49	42	24	28	37	13	41	20	43	16	16	21	27	22	37	9	21	40	25	11	7	18	19	34	25	12	23	3
	41-50 cm	18	14	13	49	14	38	12	10	21	21	13	18	17	37	15	24	3	19	26	17	12	18	11	19	19	33	9	28	21	13	28	19	26	14	11	24	15	17	14	9	8	30	15	11	2	27	17	44	13	13	12	3
	51-60 cm	11	16	0	.	4	40	7	10	11	24	8	20	9	93	9	34	1	23	9	21	9	23	3	34	5	62	6	49	9	16	8	29	13	20	7	28	11	17	6	15	3	50	7	13	1	40	7	37	10	12	6	4
	61-70 cm	3	26	3	67	2	68	2	16	3	40	2	32	3	93	2	51	1	26	5	28	2	32	0	100	1	98	2	57	3	29	5	36	3	32	1	57	5	31	2	22	2	61	2	22	0	51	2	97	4	22	2	7
	71-80 cm	3	26	0	.	1	98	0	37	2	49	1	40	3	93	0	.	0	46	1	57	1	51	0	99	0	.	0	99	1	50	2	56	2	45	1	67	1	70	1	27	0	.	1	31	0	71	0	.	1	32	1	10
	81-90 cm	1	49	0	.	0	.	0	100	0	.	0	100	0	.	0	.	0	100	0	.	0	.	0	.	0	.	0	.	1	44	0	.	0	.	0	.	1	57	1	34	1	57	0	100	0	.	0	.	0	70	0	18
	91-100 cm	0	70	0	.	0	.	0	71	0	.	0	.	0	.	0	99	0	.	0	.	0	.	0	.	0	.	0	.	0	100	0	.	0	.	0	99	0	99	0	60	0	.	0	100	0	100	0	.	0	70	0	27
	>100 cm	0	.	0	.	0	.	0	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	1	70	0	51	0	.	0	100	0	.	0	.	0	.	0	37
	total	192	8	49	44	151	19	151	6	286	11	179	11	193	31	151	17	71	12	206	10	137	10	132	12	304	26	130	21	204	10	244	13	265	10	157	15	183	11	344	6	166	22	193	8	105	10	101	30	186	7	171	2
indeterminable	n/a	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	.
	12-20 cm	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	.
	21-30 cm	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	.
	31-40 cm	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	.
	41-50 cm	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	.
	51-60 cm	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	.
	61-70 cm	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	.
	71-80 cm	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	.
	81-90 cm	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	.
	91-100 cm	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	.
	>100 cm	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	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	n/a	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	.
	12-20 cm	134	11	57	25	125	26	164	5	187	15	159	11	121	38	122	17	165	6	155	10	194	10	152	12	236	25	228	16	147	11	142	22	176	15	154	15	142	13	235	6	208	14	181	8	184	6	83	24	135	11	172	2
	21-30 cm	71	12	78	25	106	21	91	5	88	15	112	11	48	55	76	18	100	5	81	11	97	9	92	10	194	23	135	16	99	10	85	18	90	11	93	15	93	13	137	6	148	11	94	8	108	7	85	23	77	11	101	2
	31-40 cm	34	14	115	15	94	18	57	5	59	15	76	11	44	48	44	17	59	5	58	13	60	9	46	15	108	23	89	15	69	9	68	17	64	13	55	14	54	18	58	8	79	16	58	7	57	7	64	20	47	10	59	2
	41-50 cm	27	11	76	15	51	19	39	5	30	17	43	10	22	45	41	16	37	5	47	11	38	9	37	10	50	21	40	16	41	9	43	14	38	10	40	12	31	14	27	7	44	17	38	6	32	7	47	23	33	9	37	2
	51-60 cm	17	12	51	19	42	24	24	5	18	18	26	11	9	93	26	17	21	6	24	13	30	10	23	12	14	33	21	20	27	9	15	19	19	15	28	12	17	16	15	12	19	19	20	7	18	8	25	25	20	10	21	2
	61-70 cm	6	19	22	22	10	38	10	8	6	27	8	16	3	93	10	27	9	8	11	17	11	16	9	20	14	34	6	32	14	15	10	24	5	27	10	22	9	20	5	12	9	23	11	11	8	12	5	66	9	15	9	3
	71-80 cm	5	19	4	52	4	40	4	11	4	37	4	24	3	93	7	36	4	11	3	35	5	20	4	21	4	46	6	34	6	18	4	39	3	36	5	29	2	44	3	18	3	44	3	16	4	17	3	66	4	23	4	5
	81-90 cm	1	38	1	97	0	.	1	20	0	99	2	38	0	.	2	42	2	18	0	70	1	44	2	38	0	.	1	76	3	24	0	.	0	70	1	50	2	41	1	24	2	49	1	33	1	26	2	96	1	33	1	8
	91-100 cm	0	57	0	.	0	.	0	30	0	.	0	100	0	.	2	42	1	28	0	100	0	.	0	100	0	.	0	.	0	60	0	.	0	99	1	70	1	57	1	42	0	.	0	45	1	30	0	.	0	70	0	12
	>100 cm	0	.	0	.	0	.	0	44	0	.	0	100	0	.	0	99	0	35	0	70	0	100	0	100	0	.	0	.	0	57	0	.	0	.	0	99	1	70	1	41	0	.	0	70	0	71	0	.	0	.	0	18
	total	296	7	405	14	432	13	390	3	393	8	429	7	250	31	331	11	396	3	381	6	435	6	366	6	619	16	528	10	407	6	367	10	396	8	388	8	352	8	482	4	511	9	406	5	413	4	314	14	327	6	405	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. 1348830. Birmensdorf, Swiss Federal Research Institute WSL

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