A Novel Method for Evaluating Diversity of Stand Structure Based on Relationship of Adjacent Trees

doi:10.21203/rs.3.rs-331356/v1

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A Novel Method for Evaluating Diversity of Stand Structure Based on Relationship of Adjacent Trees

https://doi.org/10.21203/rs.3.rs-331356/v1

This work is licensed under a CC BY 4.0 License

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posted 22 Mar, 2021

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Background

Improving the diversity and complexity of stand structure is the basis for maintaining and increasing forest ecosystem biodiversity. Measures of stand structural diversity is important for predicting stand growth and evaluating forest management activities. Based on the relationship of adjacent trees, we present a new method for the quantitative analysis of stand structure diversity that allows comparison of stand structural heterogeneity between different stands and forest types and to quantify the impact of forest management on structural diversity.

Method:

The diversity of structural unit types was defined and then we derive a new index of forest structural diversity () according to the additivity principle of Shannon-Weiner index. The effectiveness and sensitivity to management were verified by sixteen field survey samples in different locations and six different simulated management datasets based on Pinus koraiensis broad-leaved forest survey sample.

Results

(1) The mountain rainforest in Hainan had the highest \({{S}^{\text{'}}}_{D}\) value at 5.287, followed by broad-leaved Korean pine forest in Jiaohe (2), Jiaohe (1) and oak broadleaved mixed natural forest in Xiaolongshan (2), with values of 5.144, 5.014 and 5.006, respectively. The \({{S}^{\text{'}}}_{D}\) values of plantations and natural pure forest were lower. (2) Different thinning methods and intensities reduced \({{S}^{\text{'}}}_{D}\) compared with no treatment and magnitude of the with the differences were greater as thinning intensity increased. The \({{S}^{\text{'}}}_{D}\) value of thinning from above decreased more than thinning from below at the same thinning intensity.

Conclusion

The\({{S}^{\text{'}}}_{D}\) well describes differences in stand structural diversity of different forest types and allows comparison of stand structural heterogeneity. It is also sensitive to forest management activities and to quantify the impact of forest management on structural diversity. The application of this new index \({{S}^{\text{'}}}_{D}\) could greatly facilitate forest management and monitoring.

Forestry

relationship of adjacent trees

spatial structural parameters

size differentiation

mingling

uniform angle index

structural unit types

stand structural diversity index

Table 1. Definition of terms

Term	definition
Structural unit	Reference tree i and its n nearest neighbors
Structural unit type	Classification of structural unit according to the specific values of species mingling, uniform angle index, size differentiation and number of species in the structural unit
Structural diversity index	Stand diversity measure based on tree species diversity, variation in three dimensions and diversity of stand structural unit types

Table 2. Structural unit types with the same mingling value

Value of M_i	Possible structural unit type	Possible tree species in structural unit type	No. of combination types that may occur with uniform angle index and size differentiation
0.00		1
0.25		2
0.50		2 or 3
0.75		2、3 or 4
1.00		2、3、4 or 5

Table 3 Basic characteristics of plots

No.	Plot location	Forest types	Plot size (m×m)	No. (trees/hm^-2)	No. of species	Mean DBH (cm)	Basal area (m^2.hm^-2)
1	Jianfengling, Hainan, China	Montane rainforest	30×100	820	84	29.2	54.87	0.533	0.963	0.515
2	Jiaohe, Jinlin(1), China	Pinus Koraiensis broad-leaved forest	100×100	797	19	22.4	31.67	0.491	0.828	0.493
3	Jiaohe, Jinlin (2), China	Pinus Koraiensis broad-leaved forest	100×100	1178	20	18.1	30.42	0.498	0.781	0.492
4	Xiaolongshan, Gansu (1), China	Oak Broadleaved Mixed Natural Forest	60×60	1342	49	14.6	22.79	0.491	0.806	0.493
5	Xiaolongshan, Gansu (2), China	Oak Broadleaved Mixed Natural Forest	70×70	933	33	19.5	27.85	0.492	0.806	0.509
6	Xiaolongshan, Gansu (3), China	Oak Broadleaved Mixed Natural Forest	65×50	1486	30	15.6	28.58	0.535	0.668	0.498
7	Jiulongshan, Beijing (1), China	Platycladus orientalis plantation	40×80	2331	8	10.5	20.26	0.428	0.200	0.494
8	Yiheyuanhou, Beijing (2), China	Pinus bungeana plantation	55×60	1588	1	17.7	39.2	0.383	0.000	0.495
9	Honghuaerji, Inner Mongolia (1), China	Mongolian scotch pine natural forest	100×100	940	1	21.3	33.6	0.463	0.000	0.494
10	Honghuaerji, Inner Mongolia (2), China	Mongolian scotch pine natural forest	100×100	1149	1	21.0	39.76	0.465	0.000	0.488
11	Lensahn, Germany	Beech-noble hardwood mixed forest	60×100	587	13	22.8	23.94	0.502	0.425	0.480
12	Manderscheid, Germany	Oak and beech mixed forest	80×80	381	2	31.0	28.69	0.469	0.440	0.475
13	Walsdorf, Germany	Beech and Norway spruce mixed	100×125	506	3	29.7	35.12	0.432	0.230	0.498
14	Knysna, South Africa	Subtropical evergreen natural forest	395×30	713	22	25.2	35.65	0.485	0.840	0.492
15	BialowiezaH, Poland	Temperate deciduous mixed forest	100×100	764	5	24.4	35.62	0.518	0.455	0.487
16	Sinthwat, Myanmar	Tropical mixed deciduous forest	100×100	374	56	54.1	84.09	0.512	0.883	0.500

Table 4 Measures of stand structure diversity of 16 different forest communities

No.	Plot location	No. of species in core area	Coefficient of variation of dbh ()	No. of structural unit type	Structural unit diversity ()		Stand structure diversity ()
1	Jianfengling, China	69	0.724	45	3.452	3.851	5.287
2	Jiaohe (1), China	18	0.719	137	4.521	2.452	5.014
3	Jiaohe (2), China	18	0.735	167	4.645	2.353	5.144
4	Xiaolongshan (1), China	41	0.594	117	4.474	2.808	4.326
5	Xiaolongshan (2), China	29	0.717	106	4.373	2.609	5.006
6	Xiaolongshan (3), China	29	0.514	150	4.726	2.507	3.718
7	Jiulongshan (1), China	7	0.287	96	3.864	0.569	1.272
8	Yiheyuanhou (2), China	1	0.165	20	2.604	0.000	0.430
9	Honghuaerji (1), China	1	0.368	24	2.585	0.000	0.951
10	Honghuaerji (2), China	1	0.345	24	2.619	0.000	0.904
11	Lensahn, Germany	13	0.751	92	4.150	1.222	4.034
12	Manderscheid, Germany	2	0.439	60	3.799	0.623	1.941
13	Walsdorf, Germany	3	0.376	83	3.909	0.730	1.744
14	Knysna, South Africa	21	0.512	128	4.477	2.517	3.581
15	BialowiezaH, Poland	5	0.866	138	4.535	1.020	4.811
16	Sinthwat, Myanmar	56	0.637	89	4.110	3.331	4.740

Table 5 Comparison of stand structure diversity of six different simulated thinning methods in Jiaohe, Jinlin (2), China

Plot	Measure		Density (trees /hm^-2)	No. of species in core area					No. of structural unit type	Structural unit diversity ()		Stand structure diversity ()
Jiaohe, Jinlin (2), China	Unmanaged		1178	20	0.498	0.781	0.492	0.735	167	4.645	2.353	5.144
	10%	Thinning from above	1060	18	0.499	0.752	0.503	0.509	181	4.776	2.254	3.578
	10%	Thinning from below	1060	18	0.500	0.791	0.494	0.692	156	4.625	2.393	4.856
	20%	Thinning from above	942	18	0.496	0.725	0.505	0.418	179	4.772	2.155	2.895
	20%	Thinning from below	942	18	0.488	0.802	0.498	0.644	155	4.586	2.422	4.513
	40%	Thinning from above	707	17	0.509	0.676	0.504	0.285	163	4.762	1.953	1.914
	40%	Thinning from below	707	16	0.484	0.811	0.500	0.557	132	4.465	2.4 62	3.856

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A Novel Method for Evaluating Diversity of Stand Structure Based on Relationship of Adjacent Trees

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