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–NFI5
mortality
tree species (5 classes) · higher/lower altitude zone
regional demarcation: canton
unit: 1000 m³/yr
evaluation area: accessible forest without shrub forest NFI4/NFI5
grid: 1.4 km grid, subgrids 1-5
change 2009/17–2018/26
		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
tree species (5 classes)	higher/lower altitude zone	1000 m³/yr	±%	1000 m³/yr	±%	1000 m³/yr	±%	1000 m³/yr	±%	1000 m³/yr	±%	1000 m³/yr	±%	1000 m³/yr	±%	1000 m³/yr	±%	1000 m³/yr	±%	1000 m³/yr	±%	1000 m³/yr	±%	1000 m³/yr	±%	1000 m³/yr	±%	1000 m³/yr	±%	1000 m³/yr	±%	1000 m³/yr	±%	1000 m³/yr	±%	1000 m³/yr	±%	1000 m³/yr	±%	1000 m³/yr	±%	1000 m³/yr	±%	1000 m³/yr	±%	1000 m³/yr	±%	1000 m³/yr	±%	1000 m³/yr	±%	1000 m³/yr	±%
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	.
	lower altitude zone	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	.
	higher altitude zone	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	.
spruce	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	.
	lower altitude zone	16	56	0	0	4	100	85	30	4	84	6	46	0	0	0	0	3	76	27	40	19	45	14	54	0	0	2	100	13	53	28	76	6	75	4	100	18	46	16	88	1	100	18	38	0	72	-1	100	40	47	326	15
	higher altitude zone	0	.	6	58	20	59	125	23	0	.	14	50	0	.	22	43	208	24	0	0	36	38	12	43	2	71	9	53	31	39	0	.	1	100	39	41	0	.	49	50	20	43	54	29	131	21	0	100	15	98	796	10
	total	16	56	6	58	24	52	211	18	4	84	20	38	0	0	22	43	212	24	28	40	56	29	26	35	2	71	11	47	44	32	28	76	7	64	43	38	18	46	65	43	21	42	72	23	131	21	0	256	55	43	1122	8
fir	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	.
	lower altitude zone	11	55	0	0	0	0	67	31	2	71	11	98	0	0	2	74	1	90	15	45	14	52	3	70	0	0	0	0	19	91	0	0	15	51	0	0	3	60	6	69	0	0	20	66	0	0	2	100	14	68	206	18
	higher altitude zone	0	.	0	100	6	58	14	52	0	.	1	100	0	.	0	0	12	56	4	60	20	65	2	78	0	0	3	59	11	71	0	.	0	0	5	50	0	.	0	0	9	49	2	79	5	59	1	79	0	0	95	21
	total	11	55	0	100	6	58	80	27	2	71	12	93	0	0	2	74	13	52	19	38	35	44	5	54	0	0	3	59	30	64	0	0	15	51	5	50	3	60	6	69	9	49	22	61	5	59	4	69	14	68	300	14
other 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	.
	lower altitude zone	5	80	0	.	0	0	13	40	2	100	0	0	3	72	0	0	2	82	0	0	0	0	1	100	0	.	0	100	1	100	6	65	4	52	0	0	3	74	0	100	1	100	8	64	11	46	0	0	8	54	67	18
	higher altitude zone	0	.	0	.	0	0	1	100	0	.	0	0	0	.	0	0	67	30	0	0	0	0	0	.	0	0	0	100	0	0	0	.	0	0	0	0	0	.	9	45	0	0	1	100	41	23	0	.	0	.	118	19
	total	5	80	0	.	0	0	13	37	2	100	0	0	3	72	0	0	69	29	0	0	0	0	1	100	0	0	1	81	1	100	6	65	4	52	0	0	3	74	9	45	1	100	9	59	52	21	0	0	8	54	185	14
beech	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	.
	lower altitude zone	44	37	0	0	2	100	36	53	30	46	10	49	0	.	10	76	1	58	15	45	9	59	4	77	1	100	2	68	11	41	8	61	24	38	2	100	1	82	17	35	0	100	20	36	12	53	0	0	11	51	269	13
	higher altitude zone	0	.	0	78	4	100	12	45	0	0	0	78	0	.	6	74	5	56	0	0	3	83	0	0	1	100	0	100	9	44	0	.	0	100	5	83	0	.	1	100	1	81	4	60	0	100	0	0	0	0	51	21
	total	44	37	0	78	5	74	48	41	30	46	11	47	0	.	15	55	6	47	15	45	12	48	4	77	2	71	3	59	19	30	8	61	24	38	7	67	1	82	18	34	2	67	24	31	12	53	0	0	11	51	320	11
other 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	.
	lower altitude zone	15	44	0	.	12	69	36	42	7	47	29	67	2	80	14	66	17	35	42	35	8	53	2	75	6	69	1	100	43	35	8	61	17	37	7	58	19	45	187	14	2	81	33	26	15	43	0	0	13	37	536	9
	higher altitude zone	0	.	0	0	5	100	12	34	0	0	1	76	0	.	8	47	48	27	0	0	5	51	3	78	1	100	1	79	2	50	0	.	0	0	7	43	0	.	5	48	8	59	3	45	36	41	0	0	0	0	143	15
	total	15	44	0	0	17	57	48	32	7	47	29	66	2	80	22	46	65	22	42	35	14	38	5	55	7	61	2	64	46	33	8	61	17	37	14	36	19	45	191	14	10	50	36	24	50	32	0	0	13	37	679	8
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	.
	lower altitude zone	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	0	0	.	0	0	0	0	0	0	0	0	0	.	0	0	0	0	0	.	0	0	0	0
	higher altitude zone	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	.	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	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	.
	lower altitude zone	90	27	0	0	18	77	237	18	44	38	57	41	5	56	26	51	24	30	99	23	50	26	25	38	7	66	6	49	87	30	50	47	66	25	13	56	44	31	226	15	4	60	98	22	38	30	2	135	86	27	1403	6
	higher altitude zone	0	.	6	53	35	43	164	20	0	0	16	46	0	.	35	39	339	18	4	60	65	43	16	34	4	50	13	39	53	29	0	.	1	90	56	31	0	.	64	39	38	30	63	25	213	16	2	72	15	98	1204	8
	total	90	27	6	53	52	38	400	13	44	38	72	34	5	56	61	31	364	17	104	22	116	27	41	26	12	45	19	31	139	22	50	47	67	24	70	27	44	31	290	14	42	27	162	17	251	14	3	78	101	27	2607	5

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. 1241790. Birmensdorf, Swiss Federal Research Institute WSL

back