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 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
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	50	58	57	53	603	14	29	67	406	28	2	93	19	27	314	10	226	24	93	19	837	18	20	43	85	26	184	27	63	62	66	72	35	20	104	32	72	20	36	22	1137	17	293	18	4	44	136	26	4958	6
	fir	53	42	9	89	35	78	600	15	34	65	119	36	3	100	3	47	13	24	609	18	91	19	607	20	2	49	70	82	74	36	3	65	27	47	16	31	38	54	9	27	13	33	516	16	92	68	4	52	33	36	3070	7
	pine	1	93	0	.	0	0	144	57	10	63	34	58	1	81	0	.	62	17	32	46	1	68	21	70	0	100	5	75	8	67	7	85	6	47	4	68	2	61	4	54	2	46	7	52	61	20	0	.	6	31	417	21
	larch	4	59	0	.	0	.	1	44	1	100	24	65	0	.	0	0	63	18	1	100	1	69	1	100	0	.	1	100	10	61	1	71	0	0	0	100	4	66	65	21	0	.	66	74	78	15	0	0	5	87	326	17
	Arolla pine	0	.	0	.	0	.	0	100	0	.	0	.	0	.	0	.	18	22	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	100	0	.	0	.	8	25	0	.	0	.	27	17
	other conifers	1	47	0	.	1	100	6	39	1	100	0	.	0	.	0	100	2	36	8	74	22	99	0	100	0	.	1	77	2	50	0	100	2	48	0	75	1	77	0	100	0	100	16	47	0	56	0	.	6	47	71	34
	beech	15	17	1	49	2	47	43	10	8	22	10	22	0	.	4	30	10	24	13	21	13	22	5	28	2	48	5	33	20	15	7	23	17	16	6	30	6	26	33	15	3	36	25	14	4	36	1	62	11	16	267	4
	maple	3	29	0	100	1	47	10	19	2	36	2	29	0	0	3	46	4	38	1	44	2	35	2	38	1	50	1	56	8	23	0	65	2	32	1	33	1	62	2	37	2	49	4	30	2	35	0	56	3	35	56	8
	ash	2	35	0	.	1	73	4	25	1	70	2	46	0	100	1	43	2	48	2	41	2	33	0	58	3	68	0	72	4	34	0	55	2	50	2	37	2	52	4	29	1	62	3	28	3	42	0	100	5	32	47	9
	oak	3	39	0	.	0	.	3	27	1	54	1	43	2	59	0	.	1	64	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	4	36	0	100	2	34	41	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	49	0	.	0	.	44	14
	other broadleaves	2	38	0	0	0	100	6	22	1	43	2	44	0	64	1	58	10	24	2	31	2	37	0	66	0	73	0	0	1	40	0	0	2	38	2	49	1	54	21	14	0	74	6	24	6	25	0	100	2	31	66	7
	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	171	32	61	58	95	49	1421	12	88	49	600	22	9	70	32	20	502	7	893	16	228	20	1475	15	29	33	167	42	312	20	84	48	125	40	66	16	160	27	257	9	58	18	1787	13	551	16	10	36	207	22	9387	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	931	22	717	32	602	29	8522	7	183	40	2384	17	1	100	837	24	11370	6	266	40	2344	14	384	25	680	39	1624	21	2623	14	401	35	464	27	1589	17	1032	24	2110	17	1487	20	3119	12	5622	10	320	36	1957	18	51570	3
	fir	327	34	86	48	340	40	3564	10	215	30	585	30	0	0	52	46	356	23	657	23	1802	16	341	24	73	40	303	36	516	21	42	78	514	26	449	25	455	33	303	33	495	30	1333	15	385	25	165	44	369	22	13728	5
	pine	43	60	0	.	0	0	371	29	108	35	51	64	40	100	0	.	1038	18	100	60	54	66	52	71	4	100	149	81	56	72	127	42	124	33	58	73	62	38	90	52	111	53	110	58	1241	18	0	.	242	25	4232	9
	larch	89	47	0	.	0	.	76	42	4	100	24	88	0	.	1	100	2222	10	0	0	15	57	0	0	0	.	13	100	128	49	17	65	2	100	5	100	43	60	1465	14	0	.	144	42	2507	11	2	100	43	34	6798	6
	Arolla pine	0	.	0	.	0	.	5	100	0	.	0	.	0	.	0	.	716	19	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	7	100	0	.	0	.	367	23	0	.	0	.	1095	15
	other conifers	77	52	0	.	10	76	113	37	38	100	0	.	0	.	2	100	67	37	0	0	6	47	6	100	0	.	6	100	44	42	7	100	37	57	8	75	3	72	9	92	9	100	27	52	22	63	0	.	46	50	534	16
	beech	1031	16	54	59	106	47	3718	9	718	23	907	19	0	.	225	28	607	23	756	21	979	17	422	18	234	44	407	32	1574	17	546	27	1175	18	421	20	411	21	2522	14	355	36	1727	12	521	28	83	45	1078	13	20577	4
	maple	238	22	5	73	166	43	1110	14	250	25	288	25	2	100	189	33	218	26	211	22	272	22	324	29	91	32	140	61	668	20	63	53	280	25	162	32	227	29	269	28	114	40	732	18	319	25	35	59	610	22	6985	5
	ash	222	28	0	.	142	47	519	21	141	40	417	26	10	100	118	40	275	41	306	36	157	29	39	42	207	69	39	56	420	23	58	43	153	34	195	35	218	28	480	27	101	51	517	24	302	26	25	80	296	24	5357	7
	oak	52	47	0	.	0	.	138	34	58	52	52	40	77	54	0	.	28	59	47	51	20	48	28	91	4	100	0	.	29	59	57	52	95	46	1	100	71	39	458	22	12	62	449	31	149	34	0	0	86	31	1910	11
	sweet chestnut	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	260	55	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	2655	13	0	.	1	100	65	65	0	.	0	.	2981	12
	other broadleaves	321	20	0	0	37	57	721	13	109	28	205	26	13	55	73	45	1226	17	233	28	146	28	75	37	60	62	48	48	326	30	21	54	182	38	216	34	186	32	2715	12	182	38	595	20	718	15	7	64	317	23	8731	5
	indeterminable	0	0	0	.	1	100	2	59	1	74	0	0	0	.	0	0	28	71	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	1	100	0	.	5	100	63	35
	total	3331	12	862	30	1404	24	18858	5	1826	16	4915	12	143	52	1495	18	18409	5	2577	14	5796	10	1671	13	1353	28	2730	17	6386	10	1339	20	3032	13	3103	13	2709	15	13087	6	2865	17	8763	8	12220	7	637	28	5049	10	124560	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	1046	22	1341	29	1082	30	12837	7	312	36	3802	15	0	0	1533	22	14001	7	1172	23	3321	14	2087	17	642	36	1663	22	4548	13	622	29	846	28	2586	17	943	22	2961	22	1785	22	5760	11	6358	9	552	38	2578	15	74377	3
	fir	684	31	311	41	785	38	7315	9	219	42	1050	22	0	0	232	52	840	23	1887	23	2823	15	1943	18	157	59	483	29	1856	17	100	58	532	22	1000	24	465	32	596	31	398	36	3132	13	770	30	106	50	905	20	28590	4
	pine	84	58	0	.	0	0	674	36	129	41	190	54	44	78	0	.	1063	19	120	42	128	55	46	72	0	0	51	83	64	56	158	40	212	29	25	71	228	43	86	56	117	54	80	43	637	23	0	.	461	22	4597	9
	larch	108	43	0	.	0	.	98	54	14	78	9	100	0	.	14	100	3249	10	15	100	4	100	27	100	0	.	0	0	73	55	8	100	13	100	31	100	8	100	1543	14	0	.	138	39	3481	12	11	100	114	44	8960	6
	Arolla pine	0	.	0	.	0	.	5	100	0	.	0	.	0	.	0	.	548	19	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	0	0	.	0	.	344	28	0	.	0	.	898	16
	other conifers	83	64	0	.	0	0	223	46	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	794	30
	beech	2109	17	193	49	272	36	6435	10	1281	22	1621	21	0	.	505	33	849	25	1667	18	1689	18	729	22	205	56	652	33	2917	15	1065	23	2101	15	908	26	673	22	1858	13	399	41	3335	13	297	36	174	50	1751	14	33685	3
	maple	297	29	11	71	57	46	908	15	140	44	131	32	0	0	159	35	178	37	251	26	139	27	152	40	68	42	64	47	781	18	23	84	357	25	133	34	154	49	72	44	55	43	331	22	92	59	53	52	308	21	4913	6
	ash	339	39	0	.	95	49	540	23	124	45	464	34	0	0	163	47	67	45	416	33	323	53	36	60	201	56	18	100	579	24	92	52	205	29	216	48	369	28	171	41	44	66	544	25	98	50	45	84	592	21	5739	8
	oak	263	37	0	.	0	.	258	24	59	75	85	50	167	53	0	.	93	63	183	44	151	47	42	70	0	0	0	.	30	63	76	63	63	48	8	100	281	34	355	27	44	71	358	28	43	52	9	100	247	25	2816	10
	sweet chestnut	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	112	41	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	1039	16	0	.	3	100	36	45	0	.	0	.	1190	15
	other broadleaves	168	36	0	0	22	81	312	27	66	50	110	61	0	0	74	68	250	27	217	58	77	45	3	100	9	100	0	0	147	33	9	100	50	84	38	76	182	39	770	16	15	77	427	33	159	35	0	0	256	36	3361	9
	indeterminable	0	0	0	.	0	0	14	100	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	37	58
	total	5181	12	1856	27	2313	25	29620	5	2493	18	7463	12	211	52	2680	19	21250	5	5928	13	8732	10	5065	12	1282	28	2931	18	11121	10	2195	19	4383	13	4944	14	3304	15	9499	8	2856	18	14170	8	12314	7	949	32	7215	10	169956	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	393	43	344	39	201	37	4701	10	180	56	1113	20	0	0	942	31	5150	9	542	41	1234	20	676	28	203	51	437	32	2413	18	274	51	183	44	995	26	400	35	1494	27	622	27	1648	17	2085	15	107	47	657	23	26997	4
	fir	362	32	84	66	174	49	3072	13	54	71	529	36	0	0	146	51	621	27	409	38	937	19	800	29	78	61	347	53	861	24	10	100	136	54	445	30	202	66	259	36	47	74	1198	21	216	41	66	85	467	26	11522	6
	pine	14	100	0	.	0	0	143	45	20	100	24	100	0	0	0	.	226	30	43	85	10	100	0	0	0	0	0	0	17	100	5	100	6	100	0	0	62	57	7	100	9	100	0	0	32	51	0	.	80	53	699	17
	larch	9	71	0	.	0	.	40	56	0	0	10	100	0	.	8	100	1229	16	0	0	0	0	0	0	0	.	0	0	30	72	0	0	0	0	5	100	0	0	587	26	0	.	19	73	1171	16	16	100	37	52	3162	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	.	179	34	0	.	0	.	352	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	2239	15	404	36	335	29	0	.	134	48	281	36	464	31	656	29	60	56	0	0	216	44	934	27	259	44	799	26	326	48	448	31	400	21	175	49	1051	20	97	53	42	70	1021	22	11589	6
	maple	46	66	0	0	0	0	64	38	46	63	20	58	0	0	12	100	16	75	23	100	0	0	24	100	0	0	0	0	100	39	0	0	40	51	0	0	73	83	0	0	14	100	30	60	0	0	7	100	184	41	698	18
	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	52	78	0	0	74	42	0	0	15	100	178	50	1316	15
	oak	236	41	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	0	157	41	1329	25
	sweet chestnut	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	27	61	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	843	29	0	.	0	0	45	62	0	.	0	.	915	26
	other broadleaves	62	56	0	0	6	100	82	54	6	100	75	58	0	0	6	100	58	78	8	100	0	0	0	0	0	0	0	0	10	100	0	0	8	100	9	100	142	87	26	51	14	100	336	62	22	58	0	0	22	81	892	29
	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	2468	15	453	38	425	31	10771	7	843	25	2232	16	65	100	1286	25	7816	8	1591	20	3115	14	1560	20	315	39	1000	26	4761	13	605	32	1210	22	1855	20	1816	24	3719	13	896	26	4422	12	3855	10	254	38	2804	14	60138	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	2457	20	2453	29	1941	28	26663	7	703	33	7705	14	3	75	3331	22	30835	6	2206	22	6992	13	3984	15	1546	34	3809	19	9769	13	1360	27	1559	25	5205	16	2480	20	6637	19	3930	20	11664	10	14358	9	984	36	5327	14	157902	2
	fir	1427	26	489	39	1334	36	14552	8	523	36	2283	22	3	100	432	48	1830	22	3561	19	5653	13	3691	17	310	51	1203	32	3307	16	156	59	1210	21	1910	24	1161	30	1167	28	953	31	6178	12	1462	26	341	41	1775	19	56910	4
	pine	143	55	0	.	0	0	1332	26	266	38	299	56	84	87	0	.	2389	16	296	39	193	54	118	60	4	100	205	82	146	48	298	36	349	28	86	71	355	40	188	48	239	51	197	46	1971	17	0	.	789	21	9945	8
	larch	211	39	0	.	0	.	216	42	20	72	68	63	0	.	23	100	6762	9	16	100	20	59	29	100	0	.	14	100	241	43	26	59	16	100	40	100	55	61	3660	13	0	.	366	30	7237	11	28	100	199	38	19246	6
	Arolla pine	0	.	0	.	0	.	10	100	0	.	0	.	0	.	0	.	1455	18	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	8	100	0	.	0	.	898	23	0	.	0	.	2371	14
	other conifers	188	51	0	.	10	74	458	39	269	100	0	.	0	.	2	100	68	36	8	74	296	69	6	100	0	.	7	87	379	89	65	100	43	58	9	75	3	73	75	99	9	100	93	61	23	62	0	.	56	49	2065	26
	beech	4334	15	274	47	424	34	12436	9	2411	19	2874	19	0	.	869	29	1746	22	2900	17	3337	17	1216	18	441	42	1281	30	5445	14	1878	21	4092	15	1662	24	1538	20	4812	12	932	35	6139	12	920	28	299	44	3860	13	66118	3
	maple	584	22	16	72	224	41	2092	12	438	26	442	24	2	100	362	28	417	27	486	20	412	20	502	28	160	31	205	48	1556	17	86	53	679	21	296	27	455	38	343	28	184	36	1097	16	412	25	95	48	1105	17	12652	5
	ash	702	30	0	.	238	46	1231	21	285	40	963	28	10	100	320	43	366	38	807	30	520	45	76	47	443	59	57	60	1166	22	179	45	385	27	484	35	679	25	707	27	146	52	1137	22	403	28	85	61	1070	20	12459	7
	oak	554	33	0	.	0	.	544	21	143	54	184	42	312	56	0	.	136	60	248	45	223	50	71	59	4	100	0	.	85	52	145	47	173	38	14	100	752	45	855	20	71	67	880	24	202	34	10	100	491	25	6095	9
	sweet chestnut	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	402	45	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	4575	12	0	.	4	100	148	54	0	.	0	.	5129	11
	other broadleaves	553	23	0	0	65	67	1120	15	181	30	392	35	14	55	153	45	1543	16	460	39	225	27	78	38	70	55	48	48	484	25	31	49	241	38	264	34	511	38	3532	11	211	36	1364	28	905	16	7	63	598	25	13049	6
	indeterminable	0	0	0	.	1	100	16	91	12	93	0	0	0	.	0	0	28	71	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	1	100	0	.	5	100	101	31
	total	11151	11	3232	28	4237	23	60670	5	5249	16	15210	11	428	52	5492	18	47978	5	10989	12	17872	10	9771	11	2978	25	6829	17	22579	9	4223	18	8750	12	9968	13	7988	13	26563	6	6676	16	29143	7	28940	6	1849	30	15275	9	364041	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. 1197759. Birmensdorf, Swiss Federal Research Institute WSL

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