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 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
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	.	251	25	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	19	65	0	.	0	.	211	52	0	.	0	.	481	26
	21-30 cm	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	473	22	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	81	52	0	.	0	.	299	31	0	.	0	.	853	17
	31-40 cm	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	726	21	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	95	59	0	.	0	.	483	31	0	.	0	.	1304	17
	41-50 cm	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	847	22	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	40	76	0	.	0	.	468	30	0	.	0	.	1355	17
	51-60 cm	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	650	23	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	35	60	0	.	0	.	238	37	0	.	0	.	923	19
	61-70 cm	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	293	31	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	186	39	0	.	0	.	479	24
	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	.	232	54	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	46	100	0	.	0	.	278	48
	91-100 cm	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	48	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	30	100	0	.	0	.	78	73
	>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	.	3849	16	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	270	52	0	.	0	.	2167	22	0	.	0	.	6286	13
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	.	237	23	0	.	0	.	0	.	36	91	675	21	0	.	0	.	0	.	61	97	92	57	21	84	0	.	0	.	4	100	0	.	193	29	69	60	18	54	590	21	0	.	0	.	1994	11
	21-30 cm	0	.	0	.	0	.	518	23	0	.	0	.	0	.	46	100	1440	16	0	.	11	100	0	.	71	74	208	58	117	79	0	.	0	.	8	100	0	.	457	31	88	50	50	59	1059	18	0	.	0	.	4072	9
	31-40 cm	0	.	0	.	0	.	1070	21	0	.	0	.	0	.	30	75	2756	14	0	.	9	100	0	.	88	91	288	64	236	70	0	.	0	.	30	71	0	.	586	25	175	52	62	60	1333	20	0	.	0	.	6664	9
	41-50 cm	0	.	0	.	0	.	1420	22	0	.	0	.	0	.	48	61	3382	13	0	.	0	.	0	.	40	74	238	63	100	66	0	.	0	.	70	100	0	.	680	23	138	55	142	52	1893	20	0	.	0	.	8153	8
	51-60 cm	0	.	0	.	0	.	747	25	0	.	0	.	0	.	82	60	2828	13	0	.	0	.	0	.	27	100	35	75	154	59	0	.	0	.	38	71	0	.	772	26	92	71	73	59	1817	18	0	.	0	.	6666	9
	61-70 cm	0	.	0	.	0	.	460	30	0	.	0	.	0	.	82	74	1795	20	0	.	0	.	0	.	47	100	71	100	14	100	0	.	0	.	110	79	0	.	345	30	106	60	46	78	1369	21	0	.	0	.	4445	11
	71-80 cm	0	.	0	.	0	.	296	37	0	.	0	.	0	.	0	.	880	23	0	.	0	.	0	.	19	100	0	.	98	74	0	.	0	.	45	100	0	.	219	38	0	.	159	52	666	40	0	.	0	.	2384	16
	81-90 cm	0	.	0	.	0	.	0	.	0	.	0	.	0	.	81	71	472	45	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	43	100	0	.	35	100	23	100	0	.	418	41	0	.	0	.	1072	27
	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	.	155	71	0	.	0	.	0	.	0	.	0	.	38	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	229	53
	total	0	.	0	.	0	.	4784	19	0	.	0	.	0	.	443	64	14553	11	0	.	20	100	0	.	354	71	931	51	778	54	0	.	0	.	349	72	0	.	3287	20	692	48	608	41	9288	14	0	.	0	.	36086	7
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	.	370	23	0	.	59	48	0	.	34	59	1628	12	0	.	70	51	3	100	5	100	122	34	92	45	0	.	0	.	72	52	0	.	369	24	86	48	272	38	1124	15	0	.	0	.	4304	7
	21-30 cm	0	.	0	.	0	.	570	22	0	.	186	55	0	.	64	64	3065	12	0	.	105	50	0	.	5	100	342	37	125	44	0	.	0	.	136	46	0	.	621	21	427	33	386	43	2317	16	0	.	0	.	8349	7
	31-40 cm	0	.	0	.	0	.	1045	19	0	.	332	43	0	.	84	70	4158	11	0	.	108	55	0	.	14	100	406	32	144	45	0	.	0	.	266	41	0	.	950	23	519	36	509	29	2707	15	0	0	0	.	11243	6
	41-50 cm	0	.	0	.	0	.	1253	22	0	.	433	38	0	.	126	71	5346	10	0	.	128	55	0	.	21	100	347	34	166	63	0	.	0	.	347	43	0	.	963	22	653	45	856	37	2724	14	0	.	0	.	13362	7
	51-60 cm	0	.	0	.	0	.	1568	22	0	.	442	39	0	.	76	51	4991	12	0	.	266	56	0	.	0	.	369	37	50	72	0	.	0	.	319	46	0	.	901	23	505	35	665	32	2695	15	0	.	0	.	12848	7
	61-70 cm	0	.	0	.	0	.	969	25	0	.	108	59	0	.	179	71	2858	15	0	.	0	.	0	.	0	.	64	58	84	58	0	.	0	.	165	61	0	.	612	27	208	52	775	37	1278	23	0	.	0	.	7300	9
	71-80 cm	0	.	0	.	0	.	741	30	0	.	113	79	0	.	299	62	1376	20	0	.	0	.	0	.	0	.	200	47	37	100	0	.	0	.	0	.	0	.	682	38	78	73	237	42	1012	25	0	.	0	.	4775	12
	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	.	103	71	0	.	29	100	259	43	0	.	0	.	1795	20
	91-100 cm	0	.	0	.	0	.	190	58	0	.	0	.	0	.	116	71	221	51	0	.	0	.	0	.	0	.	0	.	55	100	0	.	0	.	0	.	0	.	77	100	0	.	48	100	188	50	0	.	0	.	895	25
	>100 cm	0	.	0	.	0	.	0	.	0	.	0	.	0	.	51	100	143	71	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	129	100	0	.	49	100	64	100	0	.	0	.	436	43
	total	0	.	0	.	0	.	7018	17	0	.	1760	35	0	.	1068	52	24608	8	0	.	677	48	3	100	45	100	1955	31	792	40	0	.	0	.	1305	33	0	.	5407	17	2476	32	3825	26	14368	11	0	0	0	.	65306	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	66	53	157	44	2389	11	172	39	515	23	0	.	161	28	352	21	532	17	855	19	591	16	156	39	246	33	808	18	69	60	458	22	360	26	75	63	1101	16	240	33	1077	14	266	27	51	47	407	24	11149	4
	21-30 cm	177	40	257	40	631	32	4866	9	276	31	1386	20	0	.	366	38	722	23	893	20	1338	17	1337	18	508	40	451	32	2086	16	205	49	821	20	842	25	291	34	2073	17	494	32	2337	13	539	27	215	40	810	25	23921	4
	31-40 cm	112	43	817	31	952	26	6028	9	371	34	2075	17	0	.	465	30	1103	21	1706	19	2177	16	1536	18	751	37	737	27	3202	14	398	36	1472	22	1264	21	445	44	1886	26	516	38	3725	12	683	28	261	39	1317	19	34000	4
	41-50 cm	337	38	866	30	990	26	7737	9	354	40	2395	17	0	.	1030	25	1237	21	2199	18	2216	15	2178	15	599	36	903	27	3829	14	388	40	1388	19	1599	21	422	33	1612	23	510	37	4136	11	656	28	311	45	1872	17	39762	3
	51-60 cm	510	45	820	34	1342	30	7793	9	392	42	2262	17	0	.	1030	26	1146	23	1576	21	2799	16	2111	16	276	45	784	32	3902	14	199	48	1279	24	1917	19	410	43	1309	32	333	39	3601	12	514	40	235	43	1710	21	38247	4
	61-70 cm	129	71	509	37	468	42	4497	13	135	62	955	22	0	.	404	36	953	21	925	26	1983	22	1225	24	397	46	381	47	3035	18	123	62	332	41	832	32	316	43	701	26	263	35	2701	17	230	42	82	100	1074	27	22649	5
	71-80 cm	140	50	138	58	211	46	2255	17	160	75	658	32	0	.	293	51	633	31	510	41	878	27	801	24	78	71	419	55	1838	22	0	.	125	77	732	36	86	71	244	43	324	57	983	24	90	58	89	71	763	32	12449	7
	81-90 cm	0	.	49	100	0	.	1134	26	0	.	352	46	0	.	64	100	178	51	104	71	238	50	396	42	0	.	40	100	733	31	0	.	62	100	192	60	0	.	271	43	53	100	311	46	0	0	0	.	308	45	4483	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	.	81	100	21	100	0	.	60	100	1308	23
	>100 cm	0	.	0	.	0	.	205	74	0	.	0	.	0	.	0	.	0	.	185	71	58	100	70	100	0	.	0	.	61	100	0	.	0	.	68	100	0	.	111	100	0	.	0	.	0	.	0	.	0	.	757	35
	total	1505	33	3520	29	4750	24	37200	7	1861	32	10598	14	0	.	3914	21	6447	16	8698	15	12542	13	10309	12	2765	30	3961	25	19667	11	1381	34	5937	16	7928	16	2098	29	9396	17	2731	27	18952	9	2998	24	1244	37	8321	15	188726	3
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	800	17	0	.	0	.	1161	15	322	26	361	41	0	.	0	.	78	39	92	60	353	26	127	42	0	.	121	100	125	51	228	31	300	32	86	98	473	22	0	.	30	55	790	19	77	60	9	100	637	20	6172	6
	21-30 cm	1335	17	0	.	0	.	1677	16	457	26	665	29	0	.	0	.	160	42	309	26	875	26	181	41	0	.	86	71	418	43	417	27	469	29	11	100	948	22	0	.	164	62	1078	20	83	69	31	100	1222	19	10586	6
	31-40 cm	1591	17	0	.	0	.	2679	13	752	26	841	27	0	.	0	.	123	49	504	34	895	27	100	52	0	.	105	100	389	36	675	32	591	25	130	57	1138	22	0	.	239	60	1364	18	87	71	73	71	1456	17	13732	5
	41-50 cm	2097	16	0	.	0	.	2934	14	681	28	770	28	0	.	0	.	160	43	826	27	1210	23	225	41	0	.	0	.	215	38	796	26	812	23	177	61	1167	24	0	.	216	57	1652	19	26	72	83	82	1769	18	15815	5
	51-60 cm	1901	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	604	31	149	60	1082	23	0	.	50	100	1280	22	42	100	41	72	1708	17	14995	6
	61-70 cm	1170	21	0	.	0	.	2166	18	321	40	312	39	0	.	0	.	24	100	650	33	503	33	107	100	0	.	0	.	46	100	470	33	411	46	88	73	793	27	0	.	79	100	666	32	16	100	63	100	1240	21	9125	8
	71-80 cm	968	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	346	47	38	100	279	56	0	.	0	.	195	46	0	.	0	.	423	34	4439	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	.	0	.	0	.	0	.	45	100	489	33
	>100 cm	0	.	0	.	0	.	150	71	0	.	71	100	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	194	100	0	.	0	.	0	.	0	.	0	.	0	.	415	56
	total	10430	12	0	.	0	.	15224	10	3448	20	3991	22	0	.	0	.	829	37	3265	24	5679	18	1050	38	0	.	312	70	1759	32	3362	22	3653	20	679	53	6663	16	0	.	860	55	7112	15	332	47	300	71	8706	12	77654	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	.	20	59	0	.	127	56	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	13	100	1602	12	0	.	27	91	219	29	0	.	7	78	2014	11
	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	2639	12	0	.	83	62	289	30	0	.	0	.	3422	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	1968	12	0	.	73	62	242	33	0	.	21	100	2688	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	1565	15	0	.	53	71	170	38	0	.	17	100	2137	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	.	857	21	0	.	0	.	155	71	0	.	38	71	1204	19
	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	.	374	60	0	.	0	.	0	.	0	.	0	.	374	60
	total	0	.	0	.	0	.	0	.	0	.	0	.	475	55	0	.	1061	34	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	0	.	86	100	9984	9	0	.	236	58	1104	28	0	.	83	77	13029	8
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	846	16	66	53	157	44	4157	8	494	22	935	21	20	59	231	26	3111	9	625	17	1278	15	721	15	223	38	580	27	1046	16	297	27	757	19	522	25	561	21	3283	8	424	23	2185	11	2487	10	59	43	1051	15	26115	3
	21-30 cm	1512	15	257	40	631	32	7630	7	733	20	2237	16	95	75	475	32	6142	8	1201	16	2329	14	1518	16	584	36	1087	21	2746	14	621	24	1290	16	998	22	1274	18	5872	8	1174	20	3933	11	4586	10	247	37	2032	15	51203	2
	31-40 cm	1703	16	817	31	952	26	10823	7	1123	20	3248	14	132	65	579	26	9111	7	2210	16	3189	13	1636	17	853	34	1536	20	3972	13	1073	24	2062	17	1690	18	1591	20	5486	10	1449	22	5734	9	5534	9	334	34	2795	12	69632	2
	41-50 cm	2434	15	866	30	990	26	13344	7	1036	23	3598	14	95	64	1204	23	11180	7	3025	15	3554	12	2403	14	660	33	1488	21	4309	13	1183	22	2201	15	2192	17	1620	19	4859	10	1517	25	6839	9	5937	10	394	39	3658	12	80585	2
	51-60 cm	2411	15	820	34	1342	30	13341	7	1030	24	3472	14	52	100	1187	23	9914	7	2375	17	4551	13	2331	15	304	42	1187	24	4436	13	663	26	1883	19	2424	17	1492	20	3874	13	980	24	5619	10	5462	10	276	38	3456	13	74883	2
	61-70 cm	1299	20	509	37	468	42	8092	9	456	33	1376	18	37	100	665	30	6023	10	1576	20	2486	19	1332	23	444	42	516	38	3179	17	593	29	743	31	1194	25	1109	23	2083	13	656	27	4187	14	3079	14	145	71	2314	17	44559	3
	71-80 cm	1108	22	138	58	211	46	4266	12	377	44	903	27	45	100	591	40	3164	13	595	37	1234	23	838	24	97	61	619	40	2018	20	314	43	472	40	815	33	365	46	1401	21	402	48	1574	18	1934	19	89	71	1186	24	24755	5
	81-90 cm	451	39	49	100	0	.	1599	21	61	100	509	38	0	.	184	51	1703	21	104	71	238	50	449	39	0	.	145	77	963	27	0	.	114	71	235	52	481	43	563	28	157	52	428	37	723	29	0	.	513	34	9667	8
	91-100 cm	171	58	0	.	0	.	585	32	0	.	0	.	0	.	257	47	613	30	68	100	0	.	65	100	0	.	0	.	227	61	0	.	68	100	123	71	161	58	310	47	0	.	185	59	412	32	0	.	105	71	3352	13
	>100 cm	0	.	0	.	0	.	390	48	0	.	71	100	0	.	51	100	386	42	185	71	58	100	70	100	0	.	0	.	99	73	0	.	0	.	68	100	194	100	614	46	0	.	49	100	103	73	0	.	0	.	2338	20
	total	11935	11	3520	29	4750	24	64227	5	5310	17	16349	11	475	55	5426	19	51347	5	11963	12	18918	10	11363	11	3164	27	7159	18	22996	10	4744	18	9590	12	10261	14	8847	14	28344	7	6758	18	30732	7	30257	7	1544	33	17110	9	387089	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. 1321308. Birmensdorf, Swiss Federal Research Institute WSL

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