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.

NFI4
number of stems
tree age (in 40-year classes) · main tree species
regional demarcation: economic region
unit: n/ha
evaluation area: accessible forest without shrub forest
grid: 1.4-km grid
state 2009/17
		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
tree age (in 40-year classes)	main tree species	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	.
	spruce	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	61	0	100	0	52
	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	100	0	100	0	.	0	71
	larch	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	71	0	.	0	.	0	71
	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	100	1	100	0	.	0	90
	beech	0	.	0	.	0	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	100	0	84
	maple	0	.	0	.	0	.	0	.	0	.	0	.	0	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	100
	ash	0	.	0	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	100
	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	100	0	.	0	100	0	.	0	.	0	100	0	.	0	.	0	100	0	75	0	44
	indeterminable	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	total	0	.	0	100	0	100	0	.	0	100	0	.	0	71	0	.	0	.	0	100	0	.	0	50	1	69	1	59	0	34
=40 years	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	27	17	33	29	64	19	61	14	57	13	39	22	34	14	49	16	35	16	35	22	39	20	23	14	54	12	13	16	38	4
	fir	23	11	4	38	11	20	36	18	12	25	11	39	21	14	14	24	3	43	9	36	1	50	3	46	1	50	1	34	11	7
	pine	1	77	4	53	1	57	2	94	1	40	0	.	1	100	0	.	3	85	0	100	0	.	6	50	2	50	0	100	2	24
	larch	0	71	1	76	7	61	1	50	1	38	3	73	1	100	1	82	3	46	0	.	1	73	10	20	8	28	8	22	4	12
	Arolla pine	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	45	3	35	0	100	0	31
	other conifers	1	78	2	53	2	63	2	34	2	50	0	.	0	100	0	100	1	78	0	100	0	.	0	100	0	100	0	100	1	22
	beech	22	12	26	15	24	16	32	13	31	10	9	31	15	15	23	16	11	32	8	32	22	33	1	51	4	23	14	16	16	5
	maple	12	15	17	26	13	22	13	23	21	14	11	23	6	20	14	29	15	21	13	41	18	28	6	23	3	30	5	25	10	6
	ash	5	20	16	28	19	21	11	20	18	15	6	39	6	21	9	27	7	35	14	39	9	38	6	25	4	31	10	20	9	7
	oak	1	37	3	57	4	55	2	50	3	36	1	70	0	.	0	100	0	.	0	100	0	100	0	47	0	71	2	44	1	18
	sweet chestnut	0	.	0	.	1	78	0	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	1	100	0	.	15	22	2	21
	other broadleaves	10	14	21	43	24	26	17	18	17	13	17	28	11	18	15	24	22	19	41	32	20	27	29	13	23	16	50	10	23	5
	indeterminable	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	total	102	7	125	13	169	10	177	8	165	6	97	13	94	8	126	10	100	10	121	17	111	13	85	9	103	8	119	6	117	2
41-80 years	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	47	10	16	25	22	19	32	16	45	12	111	12	79	10	62	12	86	11	85	16	72	16	67	9	93	7	33	12	59	3
	fir	40	7	14	30	17	21	27	14	12	22	34	20	45	9	24	13	11	18	34	24	10	29	8	21	2	25	6	28	19	4
	pine	4	28	2	34	2	53	1	45	3	26	0	.	3	62	0	77	3	72	9	40	5	65	19	20	14	18	0	57	6	11
	larch	0	69	0	71	1	58	1	49	2	45	0	.	0	.	0	71	1	48	0	.	3	62	32	12	14	16	23	12	8	7
	Arolla pine	0	.	0	.	0	.	0	.	0	.	0	.	0	100	0	100	0	.	1	100	0	.	7	21	7	21	0	71	2	15
	other conifers	2	38	2	55	1	59	2	49	4	41	0	.	0	54	1	37	2	100	5	57	1	65	1	55	4	30	0	79	2	15
	beech	62	7	64	11	46	14	40	12	35	11	27	23	45	10	37	11	29	22	37	20	37	19	15	22	6	22	57	11	38	4
	maple	15	10	12	19	10	33	5	23	10	17	18	21	13	17	17	16	22	17	16	28	15	22	5	22	2	42	6	22	10	5
	ash	8	16	13	19	20	19	8	22	11	16	9	30	6	29	15	20	8	31	10	36	6	32	4	32	1	45	9	19	8	6
	oak	9	27	4	26	14	32	4	29	4	26	1	61	1	45	0	75	4	61	1	60	0	.	9	25	0	60	9	21	5	11
	sweet chestnut	0	.	0	.	1	100	0	.	0	100	0	.	0	.	0	.	0	100	0	.	0	.	1	54	0	100	46	12	6	12
	other broadleaves	11	13	13	21	13	23	7	26	13	14	5	31	6	19	9	26	17	26	10	25	12	30	18	16	10	29	54	9	17	5
	indeterminable	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	total	199	4	139	8	147	8	127	8	138	6	205	8	198	5	166	7	183	8	209	10	160	11	186	6	152	5	242	4	180	2
81-120 years	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	22	9	9	22	14	20	12	16	14	12	58	13	41	9	47	10	48	11	53	19	37	18	32	11	48	7	15	12	30	3
	fir	19	12	5	29	5	35	13	16	7	15	19	19	15	10	16	13	6	23	7	32	9	35	2	25	2	26	2	37	9	5
	pine	3	21	4	26	2	49	2	42	4	17	0	.	3	47	1	47	1	50	9	42	4	50	7	21	12	19	1	69	4	10
	larch	0	71	2	57	1	62	0	51	1	29	0	100	0	.	1	57	1	54	0	.	6	41	13	13	8	12	8	13	4	7
	Arolla pine	0	.	0	.	0	.	0	.	0	.	0	.	0	100	0	100	0	100	1	100	0	.	4	23	5	23	0	71	1	15
	other conifers	1	61	1	44	0	100	1	61	1	51	0	.	0	100	1	52	0	100	0	100	0	.	0	100	1	44	0	.	0	21
	beech	31	8	44	13	19	17	17	12	18	10	13	20	17	17	28	14	15	19	9	26	20	25	1	36	2	29	8	16	16	4
	maple	3	16	4	26	0	50	2	46	2	20	3	28	1	27	4	18	2	27	1	51	6	31	0	100	0	61	0	72	2	8
	ash	1	25	4	22	3	27	1	30	4	16	1	48	1	40	3	24	1	57	1	62	3	42	0	64	0	.	0	59	1	8
	oak	3	32	7	43	4	30	2	27	3	17	1	54	0	60	0	60	2	77	1	59	0	100	0	52	0	54	2	31	2	13
	sweet chestnut	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	100	0	100	4	20	0	20
	other broadleaves	1	37	1	34	2	76	0	63	1	33	0	.	0	45	1	36	2	50	1	71	1	42	0	52	0	72	1	31	1	15
	indeterminable	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	total	85	5	82	10	51	10	50	8	56	6	96	10	80	7	101	7	77	8	84	14	85	13	61	7	78	6	41	7	70	2
121-160 years	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	12	9	3	32	4	28	4	29	4	23	28	17	24	11	18	13	35	14	28	24	28	24	22	12	32	9	9	15	17	4
	fir	10	11	4	41	3	34	4	23	3	23	7	26	9	14	7	17	3	30	7	36	4	40	1	27	1	29	1	32	4	6
	pine	1	46	1	52	1	53	0	50	1	40	0	.	1	54	0	62	0	72	1	57	1	86	4	29	5	26	1	73	2	14
	larch	0	100	0	100	0	100	0	100	0	66	0	.	0	79	0	73	0	49	0	.	1	83	13	12	6	15	7	15	3	8
	Arolla pine	0	.	0	.	0	.	0	.	0	.	0	.	0	100	0	100	0	100	0	100	0	.	3	26	3	22	0	100	1	16
	other conifers	0	.	0	.	0	.	0	.	0	.	0	.	0	100	1	100	0	100	0	.	0	.	0	100	0	100	0	.	0	61
	beech	6	14	10	21	3	30	5	21	3	22	3	40	4	24	4	19	1	36	5	39	3	38	0	81	1	43	3	20	3	7
	maple	0	40	0	58	0	61	0	.	0	61	0	100	0	.	0	50	1	62	1	72	1	68	0	.	0	100	0	.	0	21
	ash	0	71	0	100	0	50	0	82	0	100	0	.	0	71	0	100	0	.	0	.	0	70	0	.	0	100	0	.	0	29
	oak	0	38	2	37	2	41	1	33	1	29	0	.	0	.	0	58	0	100	0	100	0	.	0	100	0	78	0	46	0	16
	sweet chestnut	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	100	0	.	1	26	0	26
	other broadleaves	0	100	0	54	0	.	0	.	0	.	0	.	0	100	0	.	1	91	0	.	0	.	0	.	0	.	0	100	0	54
	indeterminable	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	total	30	7	22	17	13	20	14	14	11	13	38	14	39	8	31	10	42	12	42	19	37	20	43	8	47	7	22	9	31	3
>160 years	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	4	17	1	85	3	37	1	73	0	71	10	25	7	17	8	24	18	16	23	29	14	30	12	14	20	10	5	14	8	5
	fir	1	20	0	.	0	100	0	100	0	63	2	32	2	24	1	37	2	32	2	47	1	39	1	38	0	41	1	28	1	10
	pine	0	.	0	.	0	.	0	.	0	.	0	.	1	49	0	.	0	70	0	70	0	.	2	54	2	38	0	59	1	27
	larch	0	.	0	.	0	.	0	.	0	.	0	.	0	100	0	.	0	62	0	.	1	90	15	11	7	15	5	13	3	8
	Arolla pine	0	.	0	.	0	.	0	.	0	.	0	.	0	100	0	100	0	79	0	100	0	.	4	23	3	19	0	100	1	14
	other conifers	0	.	0	.	0	.	0	.	0	77	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	77
	beech	1	49	1	77	0	100	0	.	0	53	1	54	0	45	0	100	1	50	1	59	2	47	0	100	0	60	1	34	0	18
	maple	0	79	0	.	0	.	0	.	0	.	0	.	0	100	0	.	0	100	0	.	0	70	0	.	0	.	0	100	0	42
	ash	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	oak	0	71	0	73	0	100	0	71	0	62	0	.	0	.	0	100	0	.	0	100	0	.	0	100	0	.	0	73	0	30
	sweet chestnut	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	100	0	.	1	34	0	33
	other broadleaves	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	100	0	.	0	100	0	71
	indeterminable	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	total	6	15	3	53	4	33	1	58	1	34	12	21	10	14	9	22	21	14	25	26	18	26	34	9	33	8	13	8	15	4
total	n/a	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	spruce	112	6	61	17	106	12	110	9	120	7	245	8	185	6	184	6	221	7	224	10	190	10	156	6	246	4	76	8	153	2
	fir	93	5	27	21	37	15	81	10	35	12	74	14	91	7	62	9	26	16	59	18	24	23	16	18	6	19	11	19	44	3
	pine	10	18	12	22	5	29	6	39	9	13	0	.	8	41	1	38	8	48	20	30	10	55	38	15	35	13	3	43	14	7
	larch	1	48	3	40	9	47	3	30	4	23	3	65	1	67	2	52	6	33	0	.	11	34	83	7	44	9	51	8	23	5
	Arolla pine	0	.	0	.	0	.	0	.	0	.	0	.	1	100	1	100	0	70	3	100	0	.	18	15	21	14	0	56	5	10
	other conifers	3	35	5	36	3	42	5	28	7	31	0	.	1	41	3	33	3	68	6	55	1	65	1	47	5	27	0	67	3	12
	beech	122	5	145	7	93	9	93	7	87	6	53	16	82	8	92	8	56	19	60	17	84	15	17	20	12	17	83	9	74	3
	maple	31	8	33	15	23	18	20	16	34	10	32	16	21	14	35	15	40	13	31	23	39	17	11	16	5	26	11	17	23	4
	ash	14	13	32	17	43	14	21	15	33	10	16	22	13	17	28	16	15	23	25	26	18	24	10	22	6	27	19	14	18	4
	oak	13	21	17	23	25	22	8	19	10	15	2	42	1	36	1	34	6	50	2	47	0	76	10	24	1	49	13	17	8	8
	sweet chestnut	0	.	0	.	2	89	0	100	0	100	0	.	0	.	0	.	0	100	0	.	0	.	2	62	0	100	67	10	9	10
	other broadleaves	23	10	36	27	38	18	24	15	31	10	23	23	17	13	24	17	42	16	52	26	32	21	48	10	33	15	105	7	41	4
	indeterminable	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.
	total	421	2	371	5	385	5	370	4	370	3	447	5	422	3	433	3	422	4	481	6	411	6	410	3	414	3	439	3	413	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. 1327295. Birmensdorf, Swiss Federal Research Institute WSL

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