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
volume of bolewood (HG 2010)
timber assortment classes (HG 2010) · main tree species
regional demarcation: canton
unit: 1000 m³
evaluation area: accessible forest without shrub forest NFI1-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
timber assortment classes (HG 2010)	main tree species	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%	1000 m³	±%
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	.
	spruce	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	.
	fir	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	.
	pine	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	.
	larch	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	.
	Arolla pine	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	.
	other conifers	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	.
	beech	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	.
	maple	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	.
	ash	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	.
	oak	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	.
	sweet chestnut	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	.
	other broadleaves	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	.
	indeterminable	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	.
smallwood	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	.
	spruce	87	52	49	60	57	53	582	14	29	67	398	29	2	93	18	29	270	11	226	24	92	20	837	18	18	47	75	28	175	29	63	62	66	72	31	21	104	32	64	22	34	23	1080	18	276	19	3	46	135	26	4772	6
	fir	53	42	9	89	35	78	584	15	34	65	119	36	3	100	3	47	13	24	609	18	91	19	607	20	2	49	70	82	70	38	3	65	27	48	15	32	38	54	8	28	13	33	503	16	91	68	4	52	33	36	3034	7
	pine	1	93	0	.	0	0	142	58	10	63	34	58	1	81	0	.	56	18	32	46	1	68	21	70	0	100	5	75	2	100	7	85	6	47	2	100	2	61	3	65	2	51	7	52	60	20	0	.	6	31	399	22
	larch	4	59	0	.	0	.	1	49	1	100	24	65	0	.	0	0	46	24	1	100	1	69	1	100	0	.	1	100	5	65	1	71	0	0	0	100	4	66	50	26	0	.	66	74	63	17	0	0	5	87	273	20
	Arolla pine	0	.	0	.	0	.	0	100	0	.	0	.	0	.	0	.	12	26	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	100	0	.	0	.	7	27	0	.	0	.	20	19
	other conifers	1	47	0	.	1	100	5	42	1	100	0	.	0	.	0	100	2	40	8	74	22	99	0	100	0	.	0	100	2	50	0	100	2	48	0	100	1	77	0	100	0	100	16	47	0	56	0	.	6	47	68	35
	beech	15	17	1	49	2	47	42	10	8	23	10	22	0	.	4	30	9	25	13	21	13	22	5	28	2	48	5	33	19	16	7	23	17	17	6	32	6	26	32	15	3	37	25	14	4	36	1	62	11	16	260	4
	maple	3	29	0	100	1	47	9	20	1	39	2	29	0	.	2	57	3	39	1	44	2	35	2	38	1	50	1	56	7	24	0	65	2	33	1	35	1	62	2	41	1	55	4	30	1	41	0	68	3	35	51	8
	ash	2	35	0	.	1	73	4	26	1	70	2	46	0	100	1	43	2	51	2	41	2	33	0	58	3	68	0	72	3	31	0	55	2	50	2	37	2	52	3	33	1	62	3	29	2	49	0	100	4	33	43	10
	oak	3	42	0	.	0	.	3	28	1	54	1	43	2	59	0	.	1	74	1	83	1	54	1	69	0	0	0	.	1	84	1	55	1	47	0	0	2	34	7	29	0	71	8	30	3	39	0	.	2	34	39	11
	sweet chestnut	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	4	45	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	39	16	0	.	0	0	1	56	0	.	0	.	43	15
	other broadleaves	2	38	0	0	0	100	5	22	1	43	2	44	0	71	1	58	9	26	2	31	2	42	0	66	0	83	0	0	1	40	0	0	2	38	2	49	1	54	18	15	0	87	4	25	4	30	0	100	1	32	58	8
	indeterminable	0	0	0	.	0	100	0	100	0	100	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	68
	total	170	32	59	59	95	49	1377	12	86	50	592	23	9	70	29	21	424	8	893	16	227	20	1475	15	27	36	156	45	285	22	84	48	125	40	59	17	160	27	226	10	55	19	1716	13	514	17	8	41	206	22	9059	4
classes 1 and 2	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	.
	spruce	926	22	650	34	602	29	7911	8	180	40	1967	17	1	100	774	26	9958	7	266	40	2235	14	384	25	630	42	1513	22	2420	15	401	35	462	27	1442	18	1032	24	1812	19	1351	22	2798	12	5155	10	226	41	1928	18	47026	3
	fir	327	34	86	48	340	40	3525	10	209	31	585	30	0	0	52	46	347	23	657	23	1797	16	341	24	73	40	303	36	501	22	42	78	509	26	413	27	455	33	287	34	475	32	1330	15	383	25	160	45	369	22	13565	5
	pine	43	60	0	.	0	0	361	30	108	35	51	64	40	100	0	.	969	20	100	60	54	66	52	71	4	100	149	81	4	82	127	42	124	33	41	95	62	38	84	56	103	57	110	58	1225	18	0	.	242	25	4054	9
	larch	89	47	0	.	0	.	71	45	4	100	24	88	0	.	1	100	1574	12	0	0	15	57	0	0	0	.	13	100	91	57	17	65	2	100	5	100	43	60	1053	16	0	.	144	42	2091	12	2	100	43	34	5281	7
	Arolla pine	0	.	0	.	0	.	5	100	0	.	0	.	0	.	0	.	496	22	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	7	100	0	.	0	.	322	25	0	.	0	.	830	16
	other conifers	77	52	0	.	10	76	80	37	38	100	0	.	0	.	2	100	58	41	0	0	6	47	6	100	0	.	6	100	40	45	7	100	37	57	3	100	3	72	9	92	9	100	27	52	22	63	0	.	46	50	484	17
	beech	1009	17	54	59	106	47	3609	9	682	24	907	19	0	.	225	28	527	24	756	21	979	17	422	18	234	44	407	32	1491	18	546	27	1164	18	380	21	411	21	2446	15	353	37	1724	12	512	28	83	45	1060	13	20085	4
	maple	238	22	5	73	166	43	1010	13	209	26	288	25	0	.	156	37	197	27	211	22	272	22	324	29	79	34	108	73	657	20	63	53	278	25	132	37	227	29	170	34	99	44	717	18	242	29	27	70	593	22	6468	5
	ash	222	28	0	.	142	47	468	20	140	41	417	26	10	100	116	41	239	46	306	36	157	29	39	42	207	69	39	56	390	24	58	43	153	34	144	39	218	28	431	30	96	53	508	24	211	27	25	80	276	26	5012	7
	oak	49	49	0	.	0	.	120	38	58	52	52	40	77	54	0	.	15	68	47	51	20	48	28	91	4	100	0	.	27	62	57	52	95	46	1	100	71	39	435	23	12	62	449	31	130	39	0	.	85	32	1832	11
	sweet chestnut	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	260	55	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	2620	13	0	.	1	100	30	80	0	.	0	.	2911	12
	other broadleaves	321	20	0	0	37	57	640	14	102	29	191	27	5	87	73	45	1068	19	233	28	141	29	75	37	54	68	44	52	290	33	21	54	181	38	139	43	180	33	2272	13	93	36	482	20	600	16	7	64	310	23	7559	6
	indeterminable	0	0	0	.	1	100	1	71	1	74	0	0	0	.	0	0	13	100	1	100	1	100	0	0	0	0	1	100	2	100	0	.	4	100	0	0	1	100	4	58	0	0	11	58	0	0	0	.	5	100	46	36
	total	3301	12	795	31	1404	24	17800	5	1732	17	4484	12	133	56	1398	19	15723	5	2577	14	5676	10	1670	13	1284	29	2583	17	5913	11	1339	20	3010	13	2700	14	2702	15	11631	6	2591	18	8299	8	10924	7	529	31	4958	10	115155	2
classes 3 and 4	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	.
	spruce	1025	22	1236	30	1082	30	11994	7	301	37	3564	16	0	0	1429	23	12951	7	1172	23	3101	15	2087	17	596	38	1621	23	4082	14	622	29	829	28	2406	18	943	22	2846	23	1699	23	5383	11	6100	10	323	42	2538	15	69930	3
	fir	684	31	311	41	785	38	7186	9	219	42	1050	22	0	0	232	52	840	23	1887	23	2809	15	1943	18	157	59	483	29	1723	18	100	58	529	22	918	26	465	32	579	32	394	37	3132	13	756	30	68	56	905	20	28155	4
	pine	84	58	0	.	0	0	659	37	129	41	190	54	44	78	0	.	1037	20	120	42	128	55	46	72	0	0	51	83	40	79	158	40	212	29	22	79	228	43	72	64	75	64	80	43	628	24	0	.	461	22	4464	9
	larch	108	43	0	.	0	.	88	59	14	78	9	100	0	.	14	100	2828	11	15	100	4	100	27	100	0	.	0	0	46	64	8	100	13	100	31	100	8	100	1316	16	0	.	138	39	3158	13	11	100	114	44	7952	7
	Arolla pine	0	.	0	.	0	.	5	100	0	.	0	.	0	.	0	.	492	21	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	0	0	.	0	.	264	32	0	.	0	.	761	17
	other conifers	83	64	0	.	0	0	221	47	139	100	0	.	0	.	0	0	0	0	0	0	78	65	0	0	0	.	0	0	126	96	41	100	3	100	0	0	0	0	49	100	0	0	50	100	0	0	0	.	3	100	791	30
	beech	2097	17	193	49	272	36	6112	9	1234	22	1621	21	0	.	505	33	828	26	1667	18	1689	18	729	22	205	56	652	33	2743	16	1065	23	2073	16	871	27	673	22	1833	13	388	42	3328	13	285	37	174	50	1741	14	32980	3
	maple	297	29	11	71	57	46	898	15	140	44	131	32	0	.	143	37	131	35	251	26	139	27	145	42	68	42	43	50	750	18	23	84	330	25	131	35	154	49	57	53	46	48	322	22	85	63	53	52	308	21	4712	6
	ash	339	39	0	.	95	49	532	23	99	51	464	34	0	0	163	47	62	48	416	33	323	53	36	60	201	56	18	100	512	25	92	52	205	29	216	48	369	28	151	45	44	66	531	26	89	55	45	84	592	21	5592	8
	oak	220	39	0	.	0	.	248	24	59	75	85	50	167	53	0	.	79	72	183	44	151	47	42	70	0	0	0	.	30	63	76	63	63	48	8	100	281	34	350	28	44	71	358	28	35	61	0	.	241	26	2720	10
	sweet chestnut	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	112	41	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	1030	16	0	.	3	100	26	50	0	.	0	.	1172	15
	other broadleaves	168	36	0	0	22	81	287	29	66	50	110	61	0	0	74	68	200	29	217	58	77	45	3	100	9	100	0	0	147	33	9	100	50	84	38	76	163	42	651	18	4	100	364	37	122	43	0	0	253	37	3034	10
	indeterminable	0	0	0	.	0	0	0	0	11	100	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	13	100	0	0	0	.	0	0	23	71
	total	5104	12	1750	28	2313	25	28229	5	2411	19	7225	12	211	52	2561	19	19561	6	5928	13	8498	11	5058	12	1236	29	2868	19	10199	10	2195	19	4309	13	4640	15	3285	15	8934	9	2693	19	13701	8	11548	8	673	34	7156	10	162285	1
classes 5 and 6	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	.
	spruce	385	44	311	42	201	37	4377	10	180	56	1073	20	0	0	890	33	4603	10	542	41	1167	21	676	28	177	56	399	34	2197	19	274	51	174	46	979	26	400	35	1443	28	622	27	1424	18	1977	15	86	56	647	23	25205	4
	fir	362	32	84	66	174	49	3024	13	54	71	529	36	0	0	146	51	621	27	409	38	937	19	800	29	78	61	347	53	776	25	10	100	136	54	429	31	202	66	253	37	47	74	1198	21	208	42	11	72	467	26	11305	6
	pine	14	100	0	.	0	0	143	45	20	100	24	100	0	0	0	.	221	30	43	85	10	100	0	0	0	0	0	0	17	100	5	100	6	100	0	0	62	57	0	0	9	100	0	0	32	51	0	.	80	53	688	18
	larch	9	71	0	.	0	.	40	56	0	0	10	100	0	.	8	100	1089	16	0	0	0	0	0	0	0	.	0	0	30	72	0	0	0	0	5	100	0	0	433	30	0	.	19	73	1101	16	16	100	37	52	2797	10
	Arolla pine	0	.	0	.	0	.	0	0	0	.	0	.	0	.	0	.	173	31	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	0	0	.	0	.	129	37	0	.	0	.	302	23
	other conifers	27	84	0	.	0	0	116	61	91	100	0	.	0	.	0	0	0	0	0	0	190	70	0	0	0	.	0	0	207	100	17	100	0	0	0	0	0	0	18	100	0	0	0	0	0	0	0	.	0	0	666	41
	beech	1179	21	26	71	44	56	2150	15	288	38	335	29	0	.	134	48	272	37	464	31	656	29	60	56	0	0	216	44	777	28	259	44	750	27	317	49	448	31	400	21	162	52	1051	20	89	57	42	70	1021	22	11138	6
	maple	46	66	0	0	0	0	50	40	46	63	20	58	0	.	12	100	16	75	23	100	0	0	0	0	0	0	0	0	90	42	0	0	40	51	0	0	73	83	0	0	0	0	19	74	0	0	7	100	184	41	626	19
	ash	139	42	0	.	0	0	169	57	19	59	79	45	0	0	38	71	22	100	85	50	38	100	0	0	33	100	0	0	163	52	29	80	24	74	70	71	90	46	38	100	0	0	50	40	0	0	15	100	178	50	1279	16
	oak	186	44	0	.	0	.	145	42	24	100	46	100	65	100	0	.	13	71	17	100	51	92	0	0	0	0	0	.	25	100	10	100	13	100	5	100	397	73	35	58	15	100	66	67	7	100	0	.	140	44	1261	26
	sweet chestnut	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	27	61	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	821	29	0	.	0	0	23	74	0	.	0	.	871	28
	other broadleaves	62	56	0	0	6	100	82	54	6	100	75	58	0	0	6	100	14	71	8	100	0	0	0	0	0	0	0	0	10	100	0	0	8	100	9	100	20	100	21	58	0	0	227	79	22	58	0	0	22	81	598	33
	indeterminable	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	2410	15	421	40	425	31	10296	8	727	27	2192	16	65	100	1234	26	7072	8	1591	20	3048	14	1536	20	288	41	961	27	4293	14	605	32	1151	22	1814	21	1694	24	3461	14	855	26	4054	12	3588	11	177	41	2777	14	56736	3
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	.
	spruce	2423	20	2245	31	1941	28	24864	7	689	34	7003	14	3	75	3111	24	27783	6	2206	22	6595	13	3984	15	1422	36	3607	20	8874	13	1360	27	1531	26	4859	17	2480	20	6166	20	3706	21	10684	10	13509	9	637	40	5248	14	146933	2
	fir	1427	26	489	39	1334	36	14318	8	516	36	2283	22	3	100	432	48	1821	22	3561	19	5634	14	3691	17	310	51	1203	32	3069	17	156	59	1202	21	1775	25	1161	30	1126	29	929	32	6162	12	1437	26	243	42	1775	19	56058	4
	pine	143	55	0	.	0	0	1305	27	266	38	299	56	84	87	0	.	2284	17	296	39	193	54	118	60	4	100	205	82	64	71	298	36	349	28	66	89	355	40	158	54	189	59	197	46	1944	18	0	.	789	21	9605	8
	larch	211	39	0	.	0	.	200	44	20	72	68	63	0	.	23	100	5536	11	16	100	20	59	29	100	0	.	14	100	171	46	26	59	16	100	40	100	55	61	2852	15	0	.	366	30	6413	12	28	100	199	38	16303	6
	Arolla pine	0	.	0	.	0	.	10	100	0	.	0	.	0	.	0	.	1173	20	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	8	100	0	.	0	.	722	24	0	.	0	.	1913	15
	other conifers	188	51	0	.	10	74	421	42	269	100	0	.	0	.	2	100	60	41	8	74	296	69	6	100	0	.	6	100	375	90	65	100	43	58	3	100	3	73	75	99	9	100	93	61	23	62	0	.	56	49	2010	26
	beech	4299	15	274	47	424	34	11912	8	2212	20	2874	19	0	.	869	29	1636	23	2900	17	3337	17	1216	18	441	42	1281	30	5030	15	1878	21	4004	15	1573	25	1538	20	4711	12	905	35	6128	12	890	29	299	44	3833	13	64463	3
	maple	584	22	16	72	224	41	1967	12	396	27	442	24	0	.	313	31	347	25	486	20	412	20	470	29	148	32	152	55	1505	17	86	53	649	22	264	29	455	38	229	36	146	38	1062	17	328	30	87	51	1088	17	11856	5
	ash	702	30	0	.	238	46	1172	21	259	43	963	28	10	100	318	44	325	42	807	30	520	45	76	47	443	59	57	60	1069	23	179	45	385	27	433	39	679	25	623	30	141	54	1092	22	302	31	85	61	1050	21	11926	7
	oak	457	34	0	.	0	.	516	22	143	54	184	42	312	56	0	.	108	71	248	45	223	50	71	59	4	100	0	.	83	53	145	47	173	38	14	100	752	45	827	21	71	67	880	24	175	39	0	.	467	26	5852	10
	sweet chestnut	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	402	45	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	4510	12	0	.	4	100	81	53	0	.	0	.	4997	11
	other broadleaves	553	23	0	0	65	67	1014	16	175	31	378	37	6	86	153	45	1291	18	460	39	219	27	78	38	63	60	44	52	449	26	31	49	240	38	187	41	365	34	2962	12	97	37	1077	32	749	17	7	63	587	26	11250	6
	indeterminable	0	0	0	.	1	100	1	71	12	93	0	0	0	.	0	0	13	100	1	100	1	100	0	0	0	0	1	100	2	100	0	.	4	100	0	0	1	100	4	58	0	0	24	61	0	0	0	.	5	100	70	34
	total	10986	11	3024	29	4237	23	57702	5	4956	17	14494	11	418	54	5221	19	42780	5	10989	12	17449	10	9739	11	2835	26	6568	17	20690	10	4223	18	8595	12	9213	14	7842	14	24252	7	6194	17	27770	7	26574	7	1387	32	15097	9	343236	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. 1385229. Birmensdorf, Swiss Federal Research Institute WSL

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