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The Relationship Between Secondary Forest and Environmental Factors

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The Relationship Between Secondary Forest and Environmental Factors www.nature.com/scientificreports OPEN The Relationship between Secondary Forest and Environmental Factors in the Received: 31 July 2017 Accepted: 15 November 2017 Southern Taihang Mountains Published: xx xx xxxx Hui Zhao1,2, Qi-Rui Wang2, Wei Fan2 & Guo-Hua Song1,3 It is important to understand the efects of environmental factors on secondary forest assembly for efective aforestation and vegetation restoration. We studied 24 20 m × 20 m quadrats of natural secondary forest in the southern Taihang Mountains. Canonical correspondence analysis (CCA) and two-way indicator hydrocarbon analysis were used to analyse the relationship between community vegetation and environmental factors. The CCA showed that 13 terrain and soil variables shared 68.17% of the total variance. The principal environmental variables, based on the most parsimonious CCA model, were (in order) elevation, soil total N, soil gravel content, slope, soil electrical conductivity, and pH. Samples were clustered into four forest types, with forest diversity afected by elevation, nutrients, and water gradients. Topographical variables afected forest assembly more than soil variables. Species diversity was evaluated using the Shannon–Wiener, Simpson’s diversity, and Pielou’s evenness indexes. The environmental factors that afected species distribution had diferent efects on species diversity. The vegetation-environment relationship in the southern region was diferent than the central region of the Taihang Mountains, and vegetation restoration was at an early stage. The terrain of the southern region, especially elevation and slope, should be considered for vegetation restoration and conservation. Forests in low mountains and hills are signifcant to forest conservation because they are rare and frequently dis- turbed by human activities1,2. Te low mountains and hills in the southern region of the Taihang Mountains are located in northwest Henan Province. Deforestation of the southern Taihang Mountains for farming and lumber has a long history, with the discovery of oracle bone scripts (14th–11th century B.C.), and is now the most popu- lous province in China. Almost all the natural forest in the southern Taihang Mountains was clear-cut during the Daoguang period of the Qing Dynasty (i.e. the early 19th century3). Te entire Taihang Mountains forest coverage rate of 20–40% (8000 B.C.) was reduced to less than 5% (A.D. 1950). Compared with other areas of the Taihang Mountains, the forests in the southern hills were the most severely damaged4. Secondary forest was restored in the late 20th century. Te Macaca Nature Reserve was established in 1982 to protect the local Macaca mulatta population and forest ecosystem. In 1998, the Macaca National Nature Reserve was merged with the Taihangshan Macaques National Nature Reserve. Further, China implemented the natural forest protection project in 1998 and stopped the logging of all natural forests5. Zhang analysed the Landsat images of 1995–2000, and indicated that the forest coverage of Southern Taihang Mountains has recovered to 32%6. Te relationship between community composition and environment, following long-term restoration of the natural secondary forest, is important to promote restoration of local vegetation, protect biological diversity, and understand the restoration process of the local ecosystem in this region. Te composition and structure of mountain vegetation is infuenced by many environmental factors, including terrain, rainfall, geographic location, soil, and geological age7. Te complexity of the terrain produces heterogene- ity in light, water, and temperature, which drives species distribution, community diferences, and landscape het- erogeneity8. Soil factors also afect plant growth and soil nutrient levels (e.g. total N, available P, and available K) are positively correlated with plant growth9. Conversely, vegetation restoration improves soil properties like soil 1Beijing Forestry University, College of Forestry, Beijing, 100083, China. 2Henan Academy of Forestry, Zhengzhou, 450008, China. 3Canvard College, Beijing Technology and Business University, Beijing, 101118, China. Correspondence and requests for materials should be addressed to G.-H.S. (email: [email protected]) SCIENTIFIC REPORTS | 7: 16431 | DOI:10.1038/s41598-017-16647-0 1 www.nature.com/scientificreports/ Environmental variable Minimum Maximum Mean Median CV Elevation (m) 310 1252 815.1 827.5 34% Slope (°) 21 70 35.4 35.5 29% Soil bulk density (g·cm−3) 0.84 1.47 1.11 1.13 14% Soil total porosity (% vol.) 44.6 68.2 58.2 57.4 10% Soil moisture content (% weight) 4 27 13 12 50% Soil electrical conductivity (dS·m−1) 1.41 9.14 3.94 3.29 56% Soil pH (−log(H+)) 4.95 7.90 6.51 6.52 12% Soil gravel content (>2 mm, % vol.) 0 28 11.3 11.5 67% Soil depth (cm) 8 20 13.4 13.5 32% Soil total N (% weight) 0.21 1.28 0.61 0.55 48% Soil organic C (% weight) 1.37 15.00 5.66 3.93 71% Table 1. Descriptive statistical analysis of the topography and soil data. organic matter content, microbial activity, nutrient levels, and physical properties (e.g. bulk density, porosity, and water content), rather promoting nutrient cycling and plant growth10. In order to explore vegetation restoration in the Taihang Mountains, studies have investigated plant com- munity composition11–13 and plant species distribution14. Yang 15 discussed the factors afecting forest growth in the Taihang Mountains. Zhang et al.16,17 evaluated the gradient of plant communities and Liu et al.18 ana- lysed secondary forest-environment relationships over long-term natural restoration processes in the central Taihang Mountains. Previous studies have largely focused on the central and northern regions of the Taihang Mountains, but few reports are available regarding the secondary forest-environment relationships in the south- ern Taihang Mountains. Te overall framework of quantitative understanding of vegetation restoration in the Taihang Mountains is incomplete. Te Taihang Mountains have a long north–south range of over 400 km and a 290 km east-west range, with high elevation in the north and low elevation in the south. Tey represent the convergence zone of the southern and northern foras of the East Asian continent, and species composition is very transitional. Te diference in terrain, climate, and latitude produces signifcant variation in north-south vegetation composition19. Compared with the central and northern regions, the damage to vegetation in the southern region is more severe4, along with soil and water loss. Te soil is barren, and the disturbance from human activities is frequent, which has made vegetation restoration difcult6,18. As such, we assumed that restoration in this area was still in the early stages, and the community composition and vegetation-environment relationship were diferent from that in the central and northern regions; therefore, the vegetation reconstruction and restoration processes used in the central and northern regions cannot be directly applied to this area. In this study, we investigated the natural secondary-deciduous broad-leaved forest community in the hills of the southern Taihang Mountains. We ana- lysed the environmental gradient, and discussed the unique community composition and its relationship with the environment to provide a scientifc basis for southern aforestation and protection projects. Tis study had three aims: frst, to comprehend the typical community composition following long-term nat- ural recovery; second, to analyse the spatial heterogeneity of water, light, temperature, and nutrients and identify the key environmental variables; and third, to reveal the environmental gradients that afect community compo- sition and species distribution, and comprehensively understand the mechanisms that create the spatial hetero- geneity of natural secondary forest assemblies in this region. Results Descriptive statistical analysis and correlation analysis for the environmental data. Te dis- persion ranges and the central tendencies of elevation, slope, and all soil variables were estimated using the min- imum-maximum and mean-median values (Table 1). Te variability of environmental data was estimated using coefcient of variation CV values. Soil bulk density, soil total porosity, and pH had low CV values (<15%), while soil gravel content and organic C had high CV values (>65%). Te R2 of the correlation between the environmental variables is shown in Table 2. Elevation and soil total N showed a signifcant, positive correlation at the 0.01 level. Slope position and soil electrical conductivity showed a signifcant, positive correlation at the 0.01 level. Soil bulk density showed a signifcant, negative correlation with soil moisture content, electrical conductivity, total N, and organic C at the 0.01 level. Soil organic C also showed a signifcant, positive correlation with soil total porosity, electrical conductivity, and total N at the 0.01 level. Tere was a clear correlation between soil nutrient variables, and soil nutrients were closely related to soil bulk density and total porosity. Tere was no signifcant correlation between soil variables and slope or aspect. Two-way indicator hydrocarbon analysis. Two-way indicator hydrocarbon analysis (TWINSPAN) clas- sifed the 24 samples into four groups representing four forest types (Fig. 1). Te names and habitats are described below. Group 1. Gleditsia microphylla-Quercus baronii forest type. Distributed from 300 to 800 m on mid and lower slopes of hills. Disturbance intensity is heavy to very heavy. Te soil
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