Species Abundance Distribution Patterns of a Toona ciliata Community in Xingdoushan Nature Reserve

doi:10.5814/j.issn.1674-764X.2019.05.004

Abstract

Abstract:

With the goal of model fitting species abundance distribution patterns of the tree, shrub and herb layers of the natural Toona ciliata community in Xingdoushan Nature Reserve, Enshi Autonomous Prefecture, Hubei Province, we used the data collected from the field survey and employed different ecological niche models. The models tested were the broken stick model (BSM), the overlapping niche model (ONM) and the niche preemption model (NPM), as well as three statistic models, the log-series distribution model (LSD), the log-normal distribution model (LND) and the Weibull distribution model (WDM). To determine the fitted model most suitable to each layer, the fitting effects were judged by criteria of the lowest value of Akaike Information Criterion (AIC), Chi-square and the K-S values with no significant difference (P>0.05) between the theoretical predictions and observed species abundance distribution values. The result showed: (1) The fitting suitability and goodness of fit of the tree, shrub and herb layers by using the three ecological niche models were ranked as: NPM>BSM>ONM. Of the three statistical models, by accepting the fitting results of the three layers, WDM was the best fitting model, followed by LND. By rejecting the fitting tests of the herb layer, LSD had the worst fitting effect. The goodness of the statistical models was ranked as: WDM>LND>LSD. In general, the statistical models had better fitting results than the ecological models. (2) T. ciliata was the dominant species of the tree layer. The species richness and diversity of the herb layer were much higher than those of either the tree layer or the shrub layer. The species richness and diversity of the shrub layer were slightly higher than those of the tree layer. The community evenness accorded to the following order: herb>shrub>tree. Considering the fitting results of the different layers, different ecological niche models or statistical models with optimal goodness of fit and ecological significance can be given priority to in studying the species abundance distribution patterns of T. ciliata communities.

Key words: Toona ciliata community, tree-shrub-herb layer, niche model, statistical model, species abundance distribution pattern, fitting model

WANG Yang, ZHU Shengjie, LI Jie, HE Xiuling, JIANG Xiongbo, ZHANG Min. Species Abundance Distribution Patterns of a Toona ciliata Community in Xingdoushan Nature Reserve[J]. Journal of Resources and Ecology, 2019, 10(5): 494-503.

Figures/Tables 8

References 46

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Model	Tree layer					Shrub layer					Herb layer
	AIC value	χ²test		K-S test		AIC value	χ²test		K-S test		AIC value	χ²test		K-S test
	AIC value	χ²	P value	D	P value	AIC value	χ²	P value	D	P value	AIC value	χ²	P value	D	P value
BSM	30.679	39.461	0^*	0.333	0.518	2.461	6.516	0.837	0.308	0.570	21.342	9.426	0.991	0.167	0.893
ONM	29.911	73.339	0^*	0.417	0.249	10.258	7.820	0.729	0.308	0.570	31.309	13.637	0.914	0.208	0.675
NPM	33.077	43.877	0^*	0.250	0.847	5.713	4.245	0.962	0.231	0.879	27.675	7.405	0.998	0.167	0.893

Model	Tree layer					Shrub layer					Herb layer
	AIC value	χ²test		K-S test		AIC value	χ²test		K-S test		AIC value	χ²test		K-S test
	AIC value	χ²	P value	D	P value	AIC value	χ²	P value	D	P value	AIC value	χ²	P value	D	P value
BSM	30.679	39.461	0^*	0.333	0.518	2.461	6.516	0.837	0.308	0.570	21.342	9.426	0.991	0.167	0.893
ONM	29.911	73.339	0^*	0.417	0.249	10.258	7.820	0.729	0.308	0.570	31.309	13.637	0.914	0.208	0.675
NPM	33.077	43.877	0^*	0.250	0.847	5.713	4.245	0.962	0.231	0.879	27.675	7.405	0.998	0.167	0.893

Vegetation layer	LSD							LND
	x value	α value	AIC value	χ²test		K-S test		S₀value	λ value	AIC value	χ²test		K-S test
	x value	α value	AIC value	χ²	P value	D	P value	S₀value	λ value	AIC value	χ²	P value	D	P value
Tree layer	0.952	3.959	-0.469	0.999	0.318	0.500	0.441	2.566	0.280	-8.530	3.989	0.408	0.429	0.541
Shrub layer	0.911	5.374	8.268	6.757	0.009^**	0.203	0.571	4.573	0.656	1.802	3.010	0.222	0.200	1.000
Herb layer	0.951	7.952	18.469	6.978	0.031^*	0.545	0.076	6.766	0.506	8.077	4.648	0.200	0.167	1.000

Vegetation layer	LSD							LND
	x value	α value	AIC value	χ²test		K-S test		S₀value	λ value	AIC value	χ²test		K-S test
	x value	α value	AIC value	χ²	P value	D	P value	S₀value	λ value	AIC value	χ²	P value	D	P value
Tree layer	0.952	3.959	-0.469	0.999	0.318	0.500	0.441	2.566	0.280	-8.530	3.989	0.408	0.429	0.541
Shrub layer	0.911	5.374	8.268	6.757	0.009^**	0.203	0.571	4.573	0.656	1.802	3.010	0.222	0.200	1.000
Herb layer	0.951	7.952	18.469	6.978	0.031^*	0.545	0.076	6.766	0.506	8.077	4.648	0.200	0.167	1.000

Vegetation layer	a value	b value	c value	WDM	AIC value	χ²test		K-S test
Vegetation layer	a value	b value	c value	WDM	AIC value	χ²	P value	D	P value
Tree layer	0	3.492	2.146	$f(x)=0.147{{x}^{1.146}}{{e}^{\frac{-{{x}^{2.146}}}{14.636}}}$	-5.516	5.598	0.133	0.286	0.938
Shrub layer	0	3.480	3.213	$f(x)=0.059{{x}^{2.213}}{{e}^{\frac{-{{x}^{3.213}}}{54.9401}}}$	2.723	2.322	0.128	0.200	1.000
Herb layer	0	4.136	3.241	$f(x)=0.033{{x}^{2.241}}{{e}^{\frac{-{{x}^{3.241}}}{99.626}}}$	8.254	4.832	0.089	0.333	0.893