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
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	.	409	17	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	96	37	0	.	0	.	266	43	0	.	0	.	771	18
	21-30 cm	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	815	18	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	178	48	0	.	0	.	329	29	0	.	0	.	1322	14
	31-40 cm	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	1001	17	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	175	49	0	.	0	.	553	28	0	.	0	.	1729	14
	41-50 cm	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	1054	19	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	75	51	0	.	0	.	543	27	0	.	0	.	1672	15
	51-60 cm	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	758	21	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	65	46	0	.	0	.	290	32	0	.	0	.	1113	16
	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	.	4980	14	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	640	33	0	.	0	.	2517	20	0	.	0	.	8138	10
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	.	276	22	0	.	31	100	0	.	44	75	919	17	0	.	0	.	0	.	61	97	114	48	28	67	0	.	0	.	21	77	0	.	292	23	80	52	29	45	657	19	0	.	0	.	2554	9
	21-30 cm	0	.	0	.	0	.	616	21	0	.	67	100	0	.	60	80	1950	14	0	.	11	100	0	.	71	74	237	52	121	76	0	.	0	.	8	100	0	.	636	26	98	45	118	56	1164	17	0	.	0	.	5156	8
	31-40 cm	0	.	0	.	0	.	1183	20	0	.	44	100	0	.	180	89	3241	13	0	.	9	100	0	.	97	84	363	53	302	59	0	.	0	.	30	71	0	.	655	22	175	52	123	52	1487	18	0	.	0	.	7891	8
	41-50 cm	0	.	0	.	0	.	1570	21	0	.	22	100	0	.	279	64	3769	12	0	.	0	.	0	.	79	62	238	63	160	50	0	.	0	.	70	100	0	.	680	23	148	52	156	48	2007	19	0	.	0	.	9178	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	.	549	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	.	4817	11
	71-80 cm	0	.	0	.	0	.	356	35	0	.	0	.	0	.	37	100	880	23	0	.	0	.	0	.	49	73	0	.	134	60	0	.	0	.	45	100	0	.	219	38	0	.	190	46	797	35	0	.	0	.	2709	15
	81-90 cm	0	.	0	.	0	.	0	.	0	.	0	.	0	.	107	59	649	36	0	.	0	.	0	.	0	.	0	.	30	100	0	.	0	.	43	100	0	.	174	55	23	100	0	.	418	41	0	.	0	.	1444	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	.	5527	18	0	.	166	100	0	.	921	48	16885	10	0	.	20	100	0	.	454	60	1081	45	981	45	0	.	0	.	366	68	0	.	3880	18	722	46	825	35	9965	13	0	.	0	.	41793	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	.	481	20	0	.	122	44	0	.	47	51	1856	11	0	.	80	46	3	100	8	75	122	34	95	44	0	.	0	.	81	48	0	.	410	22	111	38	289	36	1365	13	0	.	0	.	5070	6
	21-30 cm	0	.	0	.	0	.	661	20	0	.	212	50	0	.	67	61	3557	11	0	.	138	44	0	.	67	92	342	37	157	40	0	.	0	.	152	43	0	.	722	19	507	29	417	40	2871	14	0	.	0	.	9870	7
	31-40 cm	0	.	0	.	0	.	1328	18	0	.	465	38	0	.	84	70	4404	11	0	.	143	48	0	.	14	100	406	32	183	41	0	.	0	.	266	41	0	.	1086	21	598	33	533	28	3180	14	0	0	0	.	12689	6
	41-50 cm	0	.	0	.	0	.	1433	20	0	.	555	33	0	.	126	71	5792	10	0	.	144	50	0	.	21	100	347	34	251	53	0	.	0	.	363	42	0	.	1073	20	691	43	921	36	2980	13	0	.	0	.	14698	6
	51-60 cm	0	.	0	.	0	.	1662	21	0	.	482	36	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	2809	15	0	.	0	.	13659	7
	61-70 cm	0	.	0	.	0	.	1138	23	0	.	108	59	0	.	179	71	3079	15	0	.	0	.	0	.	0	.	64	58	209	53	0	.	0	.	165	61	0	.	638	26	208	52	890	35	1372	22	0	.	0	.	8051	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	.	767	35	155	62	237	42	1047	25	0	.	0	.	5195	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	.	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	.	8036	15	0	.	2216	30	0	.	1085	52	26862	8	0	.	818	43	3	100	109	72	1955	31	1146	39	0	.	0	.	1345	32	0	.	6107	16	2793	29	4166	24	16188	10	0	0	0	.	72829	4
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	2528	11	181	37	544	22	0	.	170	27	453	20	532	17	885	18	591	16	166	37	263	31	911	17	69	60	458	22	460	22	75	63	1235	14	304	30	1198	13	293	25	58	43	432	23	12079	4
	21-30 cm	177	40	288	37	631	32	5185	9	335	31	1469	20	0	.	375	38	1006	21	893	20	1364	16	1337	18	508	40	462	31	2223	16	205	49	821	20	1072	22	291	34	2380	15	553	29	2593	13	583	25	245	37	811	25	25808	4
	31-40 cm	112	43	859	30	952	26	6303	9	395	33	2193	17	0	.	487	29	1246	20	1706	19	2267	15	1556	18	751	37	810	26	3481	13	398	36	1472	22	1415	20	445	44	2109	23	516	38	3873	12	721	27	327	35	1364	18	35757	4
	41-50 cm	337	38	883	29	990	26	8291	9	406	37	2532	17	0	.	1051	24	1442	19	2199	18	2400	15	2265	14	599	36	915	27	4225	13	388	40	1388	19	1764	19	422	33	1792	21	510	37	4294	11	680	28	439	38	1874	17	42087	3
	51-60 cm	510	45	893	32	1342	30	8378	9	420	40	2318	17	0	.	1064	25	1235	22	1576	21	2879	16	2176	16	276	45	807	31	4282	13	199	48	1279	24	2092	18	410	43	1368	31	333	39	3648	12	539	38	400	39	1710	21	40135	4
	61-70 cm	129	71	569	35	468	42	4618	12	181	53	955	22	0	.	404	36	1074	20	925	26	1983	22	1259	23	397	46	381	47	3380	17	123	62	332	41	859	31	316	43	701	26	263	35	2761	17	306	36	82	100	1101	26	23566	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	291	40	324	57	1077	23	90	58	89	71	763	32	12925	7
	81-90 cm	0	.	49	100	0	.	1197	25	0	.	352	46	0	.	64	100	178	51	104	71	282	45	396	42	0	.	40	100	862	29	0	.	62	100	192	60	0	.	271	43	53	100	370	42	0	0	97	100	308	45	4875	11
	91-100 cm	54	100	0	.	0	.	297	45	0	.	0	.	0	.	102	80	123	71	68	100	0	.	65	100	0	.	0	.	247	60	0	.	0	.	123	71	52	100	89	100	0	.	144	71	21	100	0	.	60	100	1446	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	39352	7	2134	29	11022	14	0	.	4009	21	7390	15	8698	15	12997	12	10515	12	2775	29	4130	24	21673	10	1381	34	5937	16	8816	15	2098	29	10346	16	2854	26	19957	9	3234	23	1737	33	8423	15	199485	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	.	1166	15	327	26	361	41	0	.	0	.	78	39	92	60	353	26	127	42	0	.	121	100	125	51	228	31	285	34	86	98	483	22	0	.	30	55	797	19	89	54	9	100	642	20	6211	6
	21-30 cm	1344	17	0	.	0	.	1699	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	10699	6
	31-40 cm	1607	17	0	.	0	.	2671	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	13825	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	971	22	177	61	1180	24	0	.	264	50	1652	19	26	72	83	82	1769	18	16066	5
	51-60 cm	1965	16	0	.	0	.	3304	14	638	29	769	30	0	.	0	.	198	46	799	31	1487	26	220	49	0	.	0	.	330	48	463	32	719	29	149	60	1082	23	0	.	98	71	1323	21	84	71	41	72	1708	17	15376	6
	61-70 cm	1170	21	0	.	0	.	2203	17	355	37	312	39	0	.	0	.	24	100	650	33	503	33	107	100	0	.	0	.	46	100	470	33	513	40	88	73	793	27	0	.	142	71	700	31	16	100	63	100	1240	21	9395	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	444	40	38	100	279	56	0	.	0	.	195	46	18	100	0	.	423	34	4629	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	.	181	73	0	.	109	71	0	.	0	.	55	100	0	.	0	.	45	100	657	31
	>100 cm	0	.	0	.	0	.	150	71	0	.	71	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	112	100	0	.	287	75	0	.	0	.	63	100	0	.	0	.	0	.	683	41
	total	10622	12	0	.	0	.	15363	10	3509	20	3991	22	0	.	0	.	829	37	3265	24	5679	18	1050	38	0	.	312	70	1759	32	3362	22	4354	19	679	53	6787	16	0	.	1078	48	7313	15	452	43	300	71	8722	12	79426	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	238	27	0	.	7	78	2156	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	328	28	0	.	0	.	3652	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	271	31	0	.	21	100	2796	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	1192	26	0	.	83	77	13615	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	4451	8	508	21	1059	19	30	51	261	24	3842	7	625	17	1318	14	721	15	235	36	620	26	1160	15	297	27	742	19	648	21	572	20	3748	7	526	21	2339	10	2907	9	66	39	1081	15	28841	3
	21-30 cm	1521	15	288	37	631	32	8161	7	799	20	2413	15	95	75	503	31	7770	7	1201	16	2388	13	1518	16	646	34	1127	21	2920	14	621	24	1299	16	1243	20	1274	18	6746	7	1370	18	4287	10	5365	9	277	34	2044	15	56508	2
	31-40 cm	1719	16	859	30	952	26	11484	6	1162	20	3543	13	132	65	750	29	10260	7	2210	16	3314	13	1657	17	861	34	1684	19	4356	12	1073	24	2072	17	1841	17	1598	20	6071	9	1540	21	5967	9	6342	9	400	31	2842	12	74688	2
	41-50 cm	2453	15	883	29	990	26	14240	7	1088	22	3880	13	95	64	1455	22	12424	6	3025	15	3754	12	2490	14	699	32	1501	21	4851	12	1183	22	2359	14	2374	16	1632	19	5229	9	1612	24	7076	9	6405	9	521	34	3661	12	85882	2
	51-60 cm	2475	15	893	32	1342	30	14285	7	1058	23	3569	14	52	100	1233	22	10682	7	2375	17	4650	13	2395	15	304	42	1211	24	4886	12	663	26	1998	18	2598	16	1492	20	4142	13	1046	23	5830	10	5762	10	441	36	3456	13	78837	2
	61-70 cm	1299	20	569	35	468	42	8508	9	536	30	1376	18	37	100	665	30	6518	9	1576	20	2486	19	1366	23	466	41	538	37	3648	16	593	29	845	29	1221	25	1109	23	2169	13	718	26	4398	13	3307	13	145	71	2341	17	46901	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	2166	19	314	43	569	36	855	32	365	46	1533	20	479	43	1698	17	2118	18	89	71	1186	24	26166	5
	81-90 cm	451	39	49	100	0	.	1662	21	61	100	509	38	0	.	210	47	1921	20	104	71	282	45	449	39	0	.	145	77	1121	24	0	.	114	71	235	52	481	43	808	24	157	52	486	35	798	27	97	100	513	34	10652	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	.	303	52	0	.	181	73	123	71	161	58	348	43	0	.	303	45	439	31	0	.	105	71	3980	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	.	112	100	68	100	287	75	651	43	0	.	112	71	103	73	0	.	0	.	2830	18
	total	12128	11	3751	28	4750	24	68278	5	5643	16	17394	11	485	54	6015	18	58007	5	11963	12	19513	10	11568	11	3339	26	7478	17	25559	9	4744	18	10291	12	11207	13	8970	13	31445	6	7447	17	32496	7	33548	6	2036	30	17228	9	415285	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. 1321331. Birmensdorf, Swiss Federal Research Institute WSL

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