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
growing stock (stemwood)
altitudinal vegetation belts (NaiS; 6 classes) · diameter at breast height (10 classes)
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
altitudinal vegetation belts (NaiS; 6 classes)	diameter at breast height (10 classes)	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	.
	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	.
upper subalpine	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	.	405	17	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	96	37	0	.	0	.	222	50	0	.	0	.	723	19
	21-30 cm	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	730	17	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	178	48	0	.	0	.	312	30	0	.	0	.	1221	14
	31-40 cm	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	997	17	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	175	49	0	.	0	.	553	28	0	.	0	.	1725	14
	41-50 cm	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	1039	19	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	75	51	0	.	0	.	528	28	0	.	0	.	1643	15
	51-60 cm	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	739	21	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	65	46	0	.	0	.	258	34	0	.	0	.	1062	17
	61-70 cm	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	293	31	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	14	100	0	.	0	.	205	37	0	.	0	.	512	23
	71-80 cm	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	241	39	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	167	38	0	.	0	.	408	28
	81-90 cm	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	273	48	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	69	75	0	.	0	.	341	41
	91-100 cm	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	48	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	38	100	0	.	0	.	57	71	0	.	0	.	143	51
	>100 cm	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	88	72	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	39	100	0	.	0	.	128	58
	total	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	4854	14	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	640	33	0	.	0	.	2411	20	0	.	0	.	7906	11
subalpine	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	.	258	22	0	.	31	100	0	.	44	75	877	17	0	.	0	.	0	.	61	97	114	48	28	67	0	.	0	.	21	77	0	.	278	24	77	54	29	45	642	19	0	.	0	.	2463	10
	21-30 cm	0	.	0	.	0	.	588	21	0	.	67	100	0	.	60	80	1835	14	0	.	11	100	0	.	71	74	237	52	121	76	0	.	0	.	8	100	0	.	616	26	98	45	118	56	1150	17	0	.	0	.	4980	9
	31-40 cm	0	.	0	.	0	.	1153	21	0	.	44	100	0	.	22	110	3180	13	0	.	9	100	0	.	97	84	363	53	302	59	0	.	0	.	30	71	0	.	655	22	175	52	123	52	1461	19	0	.	0	.	7615	8
	41-50 cm	0	.	0	.	0	.	1559	21	0	.	22	100	0	.	111	55	3737	12	0	.	0	.	0	.	79	62	238	63	139	55	0	.	0	.	70	100	0	.	680	23	148	52	156	48	1997	19	0	.	0	.	8938	8
	51-60 cm	0	.	0	.	0	.	942	24	0	.	0	.	0	.	93	54	3122	13	0	.	0	.	0	.	27	100	35	75	154	59	0	.	0	.	38	71	0	.	832	24	92	71	106	51	1884	17	0	.	0	.	7325	8
	61-70 cm	0	.	0	.	0	.	532	29	0	.	0	.	0	.	82	74	1948	19	0	.	0	.	0	.	70	75	93	80	14	100	0	.	0	.	110	79	0	.	390	28	106	60	46	78	1409	21	0	.	0	.	4799	11
	71-80 cm	0	.	0	.	0	.	356	35	0	.	0	.	0	.	37	100	880	23	0	.	0	.	0	.	49	73	0	.	98	74	0	.	0	.	45	100	0	.	219	38	0	.	190	46	797	35	0	.	0	.	2673	15
	81-90 cm	0	.	0	.	0	.	0	.	0	.	0	.	0	.	107	59	649	36	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	43	100	0	.	146	63	23	100	0	.	418	41	0	.	0	.	1386	22
	91-100 cm	0	.	0	.	0	.	0	.	0	.	0	.	0	.	38	100	170	58	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	57	100	143	58	0	.	0	.	408	36
	>100 cm	0	.	0	.	0	.	36	100	0	.	0	.	0	.	0	.	237	58	0	.	0	.	0	.	0	.	0	.	38	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	311	47
	total	0	.	0	.	0	.	5424	18	0	.	166	100	0	.	595	51	16634	10	0	.	20	100	0	.	454	60	1081	45	895	48	0	.	0	.	366	68	0	.	3818	18	720	46	825	35	9901	13	0	.	0	.	40899	6
high-montane	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	.	469	20	0	.	121	45	0	.	47	51	1849	11	0	.	80	46	3	100	8	75	122	34	95	44	0	.	0	.	81	48	0	.	408	22	101	42	285	36	1331	13	0	.	0	.	4999	7
	21-30 cm	0	.	0	.	0	.	661	20	0	.	212	50	0	.	67	61	3539	11	0	.	138	44	0	.	67	92	342	37	157	40	0	.	0	.	152	43	0	.	722	19	468	30	417	40	2783	14	0	.	0	.	9725	7
	31-40 cm	0	.	0	.	0	.	1276	19	0	.	465	38	0	.	84	70	4389	11	0	.	143	48	0	.	14	100	406	32	183	41	0	.	0	.	266	41	0	.	1086	21	575	34	533	28	2965	14	0	0	0	.	12383	6
	41-50 cm	0	.	0	.	0	.	1400	20	0	.	543	34	0	.	126	71	5767	10	0	.	144	50	0	.	21	100	347	34	251	53	0	.	0	.	363	42	0	.	1073	20	680	44	921	36	2949	14	0	.	0	.	14586	6
	51-60 cm	0	.	0	.	0	.	1624	21	0	.	472	37	0	.	76	51	5267	11	0	.	284	53	0	.	0	.	369	37	120	54	0	.	0	.	319	46	0	.	995	22	523	34	752	29	2782	15	0	.	0	.	13584	7
	61-70 cm	0	.	0	.	0	.	1108	23	0	.	108	59	0	.	179	71	3079	15	0	.	0	.	0	.	0	.	64	58	209	53	0	.	0	.	165	61	0	.	612	27	208	52	890	35	1372	22	0	.	0	.	7994	9
	71-80 cm	0	.	0	.	0	.	779	29	0	.	113	79	0	.	299	62	1532	19	0	.	28	100	0	.	0	.	200	47	37	100	0	.	0	.	0	.	0	.	743	36	78	73	237	42	1047	25	0	.	0	.	5093	11
	81-90 cm	0	.	0	.	0	.	312	50	0	.	87	100	0	.	40	100	821	31	0	.	0	.	0	.	0	.	105	100	39	100	0	.	0	.	0	.	0	.	209	51	0	.	29	100	312	40	0	.	0	.	1953	19
	91-100 cm	0	.	0	.	0	.	242	50	0	.	72	100	0	.	116	71	355	41	0	.	0	.	0	.	0	.	0	.	55	100	0	.	0	.	0	.	0	.	77	100	0	.	48	100	188	50	0	.	0	.	1153	23
	>100 cm	0	.	0	.	0	.	0	.	0	.	0	.	0	.	51	100	197	58	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	129	100	0	.	49	100	64	100	0	.	0	.	491	40
	total	0	.	0	.	0	.	7870	16	0	.	2192	31	0	.	1085	52	26797	8	0	.	818	43	3	100	109	72	1955	31	1146	39	0	.	0	.	1345	32	0	.	6054	16	2633	30	4161	24	15793	10	0	0	0	.	71961	5
lower and upper montane	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	46	48	72	49	157	44	2497	11	181	37	535	23	0	.	170	27	405	20	532	17	862	19	591	16	166	37	263	31	859	17	69	60	458	22	460	22	75	63	1222	14	304	30	1198	13	293	25	58	43	432	23	11904	4
	21-30 cm	177	40	288	37	631	32	5143	9	335	31	1469	20	0	.	375	38	888	21	893	20	1345	16	1337	18	508	40	462	31	2216	16	205	49	821	20	1038	22	291	34	2363	15	553	29	2574	13	583	25	245	37	811	25	25553	4
	31-40 cm	112	43	859	30	952	26	6187	9	395	33	2193	17	0	.	487	29	1246	20	1706	19	2215	16	1536	18	751	37	810	26	3408	13	398	36	1472	22	1375	20	445	44	2074	24	516	38	3849	12	721	27	327	35	1364	18	35398	4
	41-50 cm	337	38	883	29	990	26	8198	9	406	37	2395	17	0	.	1051	24	1389	19	2199	18	2320	15	2178	15	599	36	915	27	4106	14	388	40	1388	19	1735	19	422	33	1696	22	510	37	4195	11	680	28	439	38	1874	17	41292	3
	51-60 cm	510	45	893	32	1342	30	8162	9	420	40	2262	17	0	.	1064	25	1208	22	1576	21	2859	16	2111	16	276	45	807	31	4190	13	199	48	1279	24	2062	19	410	43	1320	32	333	39	3648	12	539	38	400	39	1710	21	39581	4
	61-70 cm	129	71	569	35	468	42	4618	12	181	53	955	22	0	.	404	36	1036	20	925	26	1983	22	1259	23	397	46	381	47	3313	17	123	62	332	41	859	31	316	43	701	26	263	35	2761	17	306	36	82	100	1101	26	23460	5
	71-80 cm	140	50	138	58	211	46	2351	17	215	61	658	32	0	.	293	51	633	31	510	41	878	27	801	24	78	71	453	52	1951	21	0	.	125	77	771	35	86	71	244	43	324	57	1042	23	90	58	89	71	763	32	12844	7
	81-90 cm	0	.	49	100	0	.	1134	26	0	.	352	46	0	.	64	100	178	51	104	71	282	45	396	42	0	.	40	100	815	30	0	.	62	100	192	60	0	.	271	43	53	100	370	42	0	0	97	100	308	45	4765	12
	91-100 cm	54	100	0	.	0	.	297	45	0	.	0	.	0	.	102	80	123	71	68	100	0	.	65	100	0	.	0	.	172	74	0	.	0	.	123	71	52	100	89	100	0	.	144	71	21	100	0	.	60	100	1371	22
	>100 cm	0	.	0	.	0	.	205	74	0	.	0	.	0	.	0	.	0	.	185	71	58	100	70	100	0	.	0	.	111	71	0	.	0	.	68	100	0	.	111	100	0	.	0	.	0	.	0	.	0	.	808	33
	total	1505	33	3751	28	4750	24	38790	7	2134	29	10820	14	0	.	4009	21	7105	15	8698	15	12802	12	10343	12	2775	29	4130	24	21142	10	1381	34	5937	16	8685	15	2098	29	10090	16	2854	26	19781	9	3234	23	1737	33	8423	15	196975	2
submontane	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	811	17	0	.	0	.	1163	15	327	26	361	41	0	.	0	.	78	39	92	60	353	26	127	42	0	.	121	100	125	51	228	31	281	35	86	98	473	22	0	.	30	55	797	19	89	54	9	100	642	20	6195	6
	21-30 cm	1344	17	0	.	0	.	1687	15	463	26	665	29	0	.	0	.	160	42	309	26	875	26	181	41	0	.	86	71	418	43	417	27	478	29	11	100	948	22	0	.	213	53	1078	20	90	64	31	100	1232	19	10687	6
	31-40 cm	1607	17	0	.	0	.	2696	13	767	26	841	27	0	.	0	.	123	49	504	34	895	27	100	52	0	.	105	100	389	36	675	32	600	25	130	57	1145	22	0	.	251	57	1364	18	129	58	73	71	1456	17	13851	5
	41-50 cm	2117	16	0	.	0	.	2946	14	681	28	770	28	0	.	0	.	160	43	826	27	1210	23	225	41	0	.	0	.	215	38	796	26	855	22	177	61	1180	24	0	.	264	50	1652	19	26	72	83	82	1769	18	15950	5
	51-60 cm	1965	16	0	.	0	.	3234	14	638	29	769	30	0	.	0	.	198	46	799	31	1487	26	220	49	0	.	0	.	330	48	463	32	636	30	149	60	1082	23	0	.	98	71	1323	21	84	71	41	72	1708	17	15222	6
	61-70 cm	1170	21	0	.	0	.	2166	18	355	37	312	39	0	.	0	.	24	100	650	33	503	33	107	100	0	.	0	.	46	100	470	33	450	43	88	73	793	27	0	.	142	71	700	31	16	100	63	100	1240	21	9295	7
	71-80 cm	1042	24	0	.	0	.	974	24	217	53	131	51	0	.	0	.	33	100	84	71	356	43	37	100	0	.	0	.	45	100	314	43	370	44	38	100	279	56	0	.	0	.	195	46	18	100	0	.	423	34	4555	11
	81-90 cm	451	39	0	.	0	.	153	58	61	100	70	100	0	.	0	.	0	.	0	.	0	.	53	100	0	.	0	.	191	59	0	.	52	100	0	.	481	43	0	.	81	71	88	71	0	.	0	.	205	51	1885	19
	91-100 cm	117	71	0	.	0	.	98	71	0	.	0	.	0	.	0	.	52	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	68	100	0	.	109	71	0	.	0	.	55	100	0	.	0	.	45	100	544	32
	>100 cm	0	.	0	.	0	.	150	71	0	.	71	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	287	75	0	.	0	.	63	100	0	.	0	.	0	.	571	45
	total	10622	12	0	.	0	.	15266	10	3509	20	3991	22	0	.	0	.	829	37	3265	24	5679	18	1050	38	0	.	312	70	1759	32	3362	22	3790	20	679	53	6777	16	0	.	1078	48	7313	15	452	43	300	71	8722	12	78755	4
hyperinsubric and colline	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	.	30	51	0	.	127	56	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	13	100	1715	12	0	.	27	91	228	28	0	.	7	78	2146	10
	21-30 cm	0	.	0	.	0	.	0	.	0	.	0	.	95	75	0	.	282	41	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	35	100	2830	12	0	.	83	62	289	30	0	.	0	.	3613	10
	31-40 cm	0	.	0	.	0	.	0	.	0	.	0	.	132	65	0	.	244	51	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	7	100	2047	12	0	.	73	62	260	32	0	.	21	100	2785	10
	41-50 cm	0	.	0	.	0	.	0	.	0	.	0	.	95	64	0	.	207	44	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	30	100	1608	14	0	.	53	71	170	38	0	.	17	100	2181	12
	51-60 cm	0	.	0	.	0	.	0	.	0	.	0	.	52	100	0	.	101	53	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	882	21	0	.	0	.	155	71	0	.	38	71	1229	18
	61-70 cm	0	.	0	.	0	.	0	.	0	.	0	.	37	100	0	.	100	47	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	425	27	0	.	0	.	0	.	0	.	0	.	561	23
	71-80 cm	0	.	0	.	0	.	0	.	0	.	0	.	45	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	255	32	0	.	0	.	0	.	0	.	0	.	301	31
	81-90 cm	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	153	46	0	.	0	.	0	.	0	.	0	.	153	46
	91-100 cm	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	145	59	0	.	0	.	29	100	0	.	0	.	174	52
	>100 cm	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	411	55	0	.	0	.	0	.	0	.	0	.	411	55
	total	0	.	0	.	0	.	0	.	0	.	0	.	485	54	0	.	1061	34	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	86	100	10472	9	0	.	236	58	1132	27	0	.	83	77	13555	7
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	857	16	72	49	157	44	4386	8	508	21	1049	19	30	51	261	24	3741	8	625	17	1295	14	721	15	235	36	620	26	1108	15	297	27	739	19	648	21	561	21	3719	7	512	22	2335	10	2806	9	66	39	1081	15	28430	3
	21-30 cm	1521	15	288	37	631	32	8079	7	799	20	2413	15	95	75	503	31	7434	7	1201	16	2369	14	1518	16	646	34	1127	21	2913	14	621	24	1299	16	1210	20	1274	18	6710	7	1331	18	4269	10	5207	9	277	34	2044	15	55779	2
	31-40 cm	1719	16	859	30	952	26	11312	7	1162	20	3543	13	132	65	592	26	10179	7	2210	16	3262	13	1636	17	861	34	1684	19	4283	12	1073	24	2072	17	1802	17	1598	20	6036	10	1517	21	5943	9	6090	9	400	31	2842	12	73757	2
	41-50 cm	2453	15	883	29	990	26	14103	7	1088	22	3730	13	95	64	1288	22	12299	6	3025	15	3674	12	2403	14	699	32	1501	21	4711	12	1183	22	2244	14	2345	17	1632	19	5133	9	1602	24	6977	9	6351	9	521	34	3661	12	84590	2
	51-60 cm	2475	15	893	32	1342	30	13961	7	1058	23	3503	14	52	100	1233	22	10636	7	2375	17	4629	13	2331	15	304	42	1211	24	4794	12	663	26	1915	19	2568	16	1492	20	4094	13	1046	23	5830	10	5704	10	441	36	3456	13	78004	2
	61-70 cm	1299	20	569	35	468	42	8423	9	536	30	1376	18	37	100	665	30	6479	9	1576	20	2486	19	1366	23	466	41	538	37	3581	16	593	29	781	30	1221	25	1109	23	2142	13	718	26	4398	13	3307	13	145	71	2341	17	46621	3
	71-80 cm	1183	22	138	58	211	46	4459	12	432	40	903	27	45	100	629	38	3320	12	595	37	1262	23	838	24	127	52	652	39	2130	20	314	43	496	38	855	32	365	46	1461	21	402	48	1664	17	2118	18	89	71	1186	24	25874	5
	81-90 cm	451	39	49	100	0	.	1599	21	61	100	509	38	0	.	210	47	1921	20	104	71	282	45	449	39	0	.	145	77	1045	26	0	.	114	71	235	52	481	43	780	25	157	52	486	35	798	27	97	100	513	34	10484	8
	91-100 cm	171	58	0	.	0	.	637	30	0	.	72	100	0	.	257	47	748	28	68	100	0	.	65	100	0	.	0	.	227	61	0	.	68	100	123	71	161	58	348	43	0	.	303	45	439	31	0	.	105	71	3792	12
	>100 cm	0	.	0	.	0	.	390	48	0	.	71	100	0	.	51	100	522	36	185	71	58	100	70	100	0	.	0	.	150	59	0	.	0	.	68	100	287	75	651	43	0	.	112	71	103	73	0	.	0	.	2719	19
	total	12128	11	3751	28	4750	24	67349	5	5643	16	17168	11	485	54	5689	18	57280	5	11963	12	19319	10	11396	11	3339	26	7478	17	24943	9	4744	18	9727	12	11076	13	8960	13	31074	6	7284	17	32316	7	32923	7	2036	30	17228	9	410050	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. 1321320. Birmensdorf, Swiss Federal Research Institute WSL

back