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Associations between plant composition/diversity and the abiotic environment across six vegetation types in a biodiversity hotspot of Hainan Island, China

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Exploring the associations between vegetation and abiotic environments might increase our understanding of biodiversity formation mechanisms. Here, we explore variation in plant composition/diversity and their abiotic determinants across six vegetation types in a biodiversity hotspot of Hainan Island, China.


We established twelve 1-ha permanent plots, two in each of the six old-growth forest types. All woody stems (dbh ≥ 1 cm) and six soil and two microclimatic factors were measured. Associations between the abiotic factors and plant composition/diversity were analyzed by a spatial regressive model.


Plant diversity/composition changed with forest types. The key factors correlated with species composition in deciduous monsoon forest were canopy openness and soil water content. Soil total nitrogen and pH were the vital determinants of diversity in coniferous forest. Soil water content, phosphorus and canopy openness were associated with higher diversities in lowland- and montane- rain forests. Soil organic matter and pH were the major factors influencing composition in the montane evergreen forest, whereas air temperature and soil total nitrogen were associated with the lowest diversity of the stunting statured montane dwarf forest.


Variation patterns of plant composition/diversity across different forest types were closely associated with the changes in the six soil and two microclimatic factors within each forest.

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Tropical deciduous monsoon rain forest


Tropical coniferous forest


Tropical lowland rain forest


Tropical montane rain forest


Tropical montane evergreen forest


Tropical montane dwarf forest


Canopy openness


Soil water content


Soil organic matter


Soil total nitrogen


Soil total phosphorus


Soil available phosphorus


Air temperature


Canonical correspondence analysis


Spatial simultaneous autoregressive error model estimation


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This work was supported by the national forestry research project for public welfare (201304308) and the National Natural Science Foundation of China (30430570). We appreciate the constructive comments by Dr. Antony Van der Ent and two anonymous referees, which have greatly improved the earlier versions of this manuscript. We also would like to extend our thanks the many local staff in the Bawangling National Nature Reserve who helped us in conducting the hard fieldwork.

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Correspondence to Runguo Zang.

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Fig. 6

Non-metric multidimensional scaling analysis showing the relationships between the 6 soil variables and species abundance using “Bray-Curtis” dissimilarity across the six old-growth forest types (data from all the 300 plots combined). The black solid dots represent tropical deciduous monsoon rain forest (TDMRF); the grey plus signs represent tropical coniferous forest (TCF); the blue hollow dots represent tropical lowland rain forest (TLRF); the yellow solid triangles represent tropical montane rain forest (TMRF); the green hollow triangles represent tropical montane evergreen forest (TMEF); the red multiplication signs repr esent tropical montane dwarf forest (TMDF). Canopy openness (CO, %), Soil water content (SWC, %), Soil organic matter (SOM, g kg−1), Soil total nitrogen. (TN, g kg−1), Soil total phosphorus (TP, g kg−1), Soil available phosphorus (AP, mg kg−1) and Air temperature (AT, °C) (GIF 499 kb)

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(TIF 184 kb)


Appendix 1

Table 5 The dominance of 54 species were selected using calculating importance values (IV = Relative frequency + Relative density + Relative dominance) across the six vegetation types

Appendix 2

Fig. 5
figure 5

Correlograms for original richness (capital letter) and residuals (small letter) of the SAR models for different environmental factors across the six old-growth forest types

Appendix 2 showed species richness data for different environmental variables 'spatial autocorrelation at 3 distance classes, and the spatial autocorrelations among the three spatial lag order were exist to some extent across the six vegetation types (capital letter). Spatial autocorrelation in the residuals was almost removed from the species richness data of the addition 8 environmental variables, suggesting that there was no statistical bias in the SAR models (small letter).

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Jiang, Y., Zang, R., Letcher, S.G. et al. Associations between plant composition/diversity and the abiotic environment across six vegetation types in a biodiversity hotspot of Hainan Island, China. Plant Soil 403, 21–35 (2016).

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