Response of understory vegetation, tree regeneration, and soil quality to manipulated stand density in a Pinus massoniana plantation

Global Ecology and Conservation 20 (2019) e00775

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Original Research Article

Response of understory vegetation, tree regeneration, and soil quality to manipulated stand density in a Pinus massoniana plantation Ashfaq Ali a, Dong Dai a, e, Kashif Akhtar b, Mingjun Teng a, Zhaogui Yan a, Nicolas Urbina-Cardona c, Jana Mullerova d, Zhixiang Zhou a, * a

College of Horticulture and Forestry Sciences/Hubei Engineering Technology Research Center for Forestry Information, Huazhong Agricultural University, Wuhan, China Institute of Nuclear Agricultural Sciences, College of Agriculture and Biotechnology, Zhejiang University, Hangzhou, China c Ecology and Territory Department, Faculty of Rural and Environmental Studies, Pontificia Universidad Javeriana, Colombia d Department of GIS and Remote Sensing, Institute of Botany, The Czech Academy of Sciences, Pruhonice, Czech Republic e ECNU-Alberta Joint Lab for Biodiversity Study, Tiantong Forest Ecosystem National Observation and Research Station, School of Ecology and Environmental Sciences, East China Normal University, Shanghai, China b

a r t i c l e i n f o

a b s t r a c t

Article history: Received 14 June 2019 Received in revised form 3 September 2019 Accepted 3 September 2019

Tree density affects species diversity in forest plantations. Understory species diversity, tree regeneration, and soil physicochemical characteristics were assessed under three planting densities of Pinus massoniana in Taizishan Mountains, Hubei, China. There was a higher degree of shrub and herb species diversity in lower density stands. Total species richness was higher for herbs (n ¼ 42) than for shrubs (n ¼ 30) but the two groups exhibited a similar pattern with greater species richness at lower stand density. Changes in community structure and composition were more frequent in high density stands. Community structure in low and medium density stands was more similar to one another than to high stand densities for both herbs and shrubs. The regeneration status of tree species was more abundant in low and medium density stands. Low and medium density stands had significantly more favorable chemical properties such as soil organic matter, total phosphorus, available phosphorus, and nitrogen, as well as on physical soil properties such as non-capillary pores and minimum water holding capacity. Lower planting density was beneficial with regard to natural regeneration, plant species diversity, and soil quality. Reducing tree density of existing high-density P. massoniana plantations can promote both understory plant species diversity and tree regeneration to sustain forest ecosystem services. © 2019 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

Keywords: Forest plantations Stand density Natural regeneration Soil properties Ground vegetation

* Corresponding author. College of Horticulture and Forestry Sciences, Huazhong Agricultural University, No. 1 Shizishan, Hongshan District Wuhan, 430070, Wuhan, Hubei, PR China. Tel.: þ86 27 8728 4232; fax: þ86 27 8728 4232. E-mail address: [email protected] (Z. Zhou). https://doi.org/10.1016/j.gecco.2019.e00775 2351-9894/© 2019 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/ licenses/by-nc-nd/4.0/).

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1. Introduction Forest plantations are usually established by planting or seeding or sometimes both, and are established for a variety of reasons, including timber production, and soil and water conservation (Aubin et al., 2008). They are becoming an increasingly ubiquitous land use type, but an improved understanding of their potential and ecological functioning is necessary for planning and implementing social and ecologically sustainable land use policies to enhance critical ecosystem services (Goldman et al., 2008). As well as being a source of timber and contributing to soil and water conservation, forest plantations may aid restoration in degraded areas where natural regeneration may otherwise be inhibited, and can contribute to biodiversity conservation (Bremer and Farley, 2010; Duan et al., 2009), as well as providing a wide range of other ecosystem services. Globally, 277.9 million ha are occupied by plantations, with 62% of these in Asia due to increasing demand for timber production and energy in the region (Payn et al., 2015). Silvicultural practices and site management have been regarded as key factors driving stand dynamics and biodiversity of the planted sites. When evaluating the sustainability of forest management, the natural forest is considered a reference state (Paillet et al., 2010); on this basis, the effect of plantations on community succession and biodiversity has been shown to be negative (Lima and Vieira, 2013; Paillet et al., 2010). To understand the effects of different forest plantations on community regeneration and biodiversity, studies have taken into account plantation age as well as land use transition and history, tree species, surrounding vegetation, available propagules in the surrounding forests, seed dispersal, and extent of soil degradation (Bremer and Farley, 2010; Coll et al., 2011; Duan et al., 2009). Cao et al. (2011) suggested that biodiversity significantly increases over time, but other studies conducted in different parts of Europe have found that while species richness increases within the first 20 years of plantation, this is followed by a decline (Paillet et al., 2010). China has many large forest plantations, mostly occupied by native tree species, and massive new plantations are in progress under various national programs. The primary goal of such planting projects is to mitigate environmental problems caused by the substantial loss of forests and degraded landscapes, with secondary goals of forest conservation and restoration of degraded soils (Brockerhoff et al., 2008). In addition, there is increasing demand for timber and fuel, leading to overexploitation of natural forests and loss of biodiversity (Cao et al., 2011; Xue et al., 2014). China has a rich biota including 27,000 species of higher plants with 7000 woody species (Brockerhoff et al., 2008). In most biodiversity spots identified in China, threats to biodiversity are important considerations, and steps for conservation are required. Successful conservation and maintenance of habitat is a long-term process from plant establishment until successful self-sustainability and natural ecosystem functioning (Chen and Cao, 2014). Initial field investigations show that diversity and understory plant species composition in plantations are poor, and survival and establishment of tree seedlings is unremarkable (Ballabha et al., 2013). In addition, under such plantations, a layer of dry soil can be observed as the water consumed by planted exotic trees exceeds soil water recharge (Jiao et al., 2012). Ultimately, this could lead to soil and biodiversity degradation, primarily because of the increasing water scarcity. Ecological restoration methods that reflect natural processes could offer a more adaptive and appropriate approach (Chirino et al., 2006; Jiao et al., 2012). In forests, the herbaceous layer contributes to carbon stock, primary production, nutrient supply, and species diversity. It also serves as a habitat and food source for other forest organisms (Ahmad et al., 2018; Whigham, 2004). Forest understory species are regarded as ecological indicators due to their quick response to changing environmental conditions (Von Oheimb €rdtle, 2009). As such, factors affecting species composition of the understory assemblage can serve as important inand Ha dicators. A number of important determinants affect the establishment, survival rate, and adaptability of plants species,  ski, 2002; Tinya including soil physicochemical properties such as nutrient content, pH, and moisture (Dzwonko and Gawron et al., 2009). Soil quality also determines the mycorrhizal community and the microbes present in the soil, thus indirectly rez-Ramos et al., 2008). Propagule source mainly affects herbaceous influencing species composition of the herb layer (Pe  a m et al., species composition, since dispersal distance is a limiting factor in forests, even for wind-dispersed species (Ad 2013). Additionally, some silvicultural operations such as shelterwood systems favor extensive clear-cutting, further  a m et al., 2013). Stand characteristics are greatly affected by species increasing the importance of propagule source (Ad composition and the structure of the shrub and overstory layers as well (Rogers et al., 2008). Tree density and structure of the canopy and shrub layers determine light availability and moisture content for the understory layer, and quantity and quality of litter also influence soil temperature, moisture, pH, carbon, and nitrogen ratios (Barbier et al., 2008; Tinya et al., 2009). Stand age and density are the two most important factors affecting stand structure and composition, species richness and composition, and herb and shrub cover. Increasing canopy openness ensures adequate resource availability for understory plant development (Wilson and Puettmann, 2007). Meanwhile understory plants protect the soil surface from rain and effects of through-fall, minimizing detachment of the soil particles, increasing the roughness of the soil surface, and helping to reduce the transportation capacity by the roots, resulting in strong influences on soil erosion. An understanding of the effects of tree density on the regeneration of this community, its stability, and its species diversity is advisable to maximize these benefits (Wilson and Puettmann, 2007). A positive response between old-growth coniferous trees and different density reduction treatments was demonstrated by Latham and Tappeiner (2002), where they found a remarkable improvement in tree vigor in response to reducing stand density. Other studies found no fundamental change in the pattern of understory succession or understory herb and shrub biomass after a seventeen-year density reduction treatment in Picea spp. forests in Oregon (Chen and Cao, 2014). However, there are few reports on the effect of stand density on understory vegetation and soil characteristics in P. massoniana plantations. In this study, we aim to provide a baseline for sustainable management of P. massoniana plantations so as to

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enhance biodiversity conservation and ecosystem services. We address the specific issues of planting density by investigating the effects of three density levels on understory species diversity, soil physicochemical properties, and tree species regeneration. We also attempted to assess the influence of plantation density on soil physicochemical characteristics and their role in maintaining soil quality. 2. Materials and methods 2.1. Study area This study was conducted at Taizishan Forestry Administration Bureau (TFAB; 112 480 E to 113 030 E, and 30 480 N to 31020 N; 454 m a.s.l.), located in Jingming City, Hubei Province, central China (Fig. 1). It is located in a subtropical humid monsoon climate zone with cold winters and hot and rainy summers. The annual mean temperature is 16.4  C, with an average annual rainfall of 1090 mm. The period with the highest rainfall is from July to September. The forests in the area include evergreen coniferous, broad-leaved, and mixed coniferous broad-leaved types. The mean soil bulk density is 2.3 g cm3, with a lower than average surface soil layer density. There are three major soil types: yellow-brown soil, mountain yellow-brown soil, and yellow-cinnamon soil. An extended plantation of P. massoniana (an endemic pine species) was established over the entire study area in 1957. Major herbaceous species in the understory include Carex stenophylloides and Artemisia sacrorum, and the shrub layer is dominated by Lonicera japonica, Rosa xanthina, and L. microphylla (Ali et al., 2019; Chen et al., 2019). 2.2. Data collection Three planting density classes, including low (LD ¼ 1212 trees ha1), medium (MD ¼ 1745 trees ha1), and high (HD ¼ 2519 trees ha1) were selected during MayeSeptember 2017. Within the three stand density classes, three experimental blocks of 30  30 m were established. The diameter at breast height (DBH) and height (H) of all trees were measured in each block, and all individual trees within each block with DBH greater than 5 cm were counted (Cao et al., 2011; Chen and Cao, 2014). Within each block, forty-five 5  5 m plots were analyzed for understory diversity. We determined species diversity, species richness, and Simpson, ShannoneWiener, and Pielou indices using the following formulas: Species richness as the richness index Simpson index (S):

Fig. 1. Map of the study area representing the density classes in Taizishan Forestry Administration Bureau, Hubei Province, China.

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D¼1 

X

ðPiÞ2

(1)

ShannoneWiener index: 0

H ¼

X ðPiÞ1nðpiÞ

(2)

Pielou index:

J sw ¼



P

Pi 1n Pi 1nS

(3)

All shrub and herb species were identified and their coverage recorded. To assess species composition and the regeneration status of saplings and seedlings at the three densities, 75 separate plots of 2  2 m for each density were established. The density of each vegetation layer, i.e., the number of trees, saplings, and seedlings were recorded as described in Liu et al. (2015). We determined the regeneration status of all tree species and recorded the understory plant density, frequency, abundance, relative density, relative frequency, relative abundance, and importance value (IV) as described in Rahman et al. (2011). Regeneration status was regarded as good if the number of seedlings > number saplings > number of trees, fair if the number of seedlings > number saplings  number of trees, poor if the species were present only in a sapling stage and no seedlings were observed, and not regenerating if only adult trees of a particular species was present (Ballabha et al., 2013). 2.3. Soil investigation Soil samples were randomly collected at nine different points within the 2  2 m subplot in each treatment using a corer from the upper 40 cm (0e10, 10e20, and 20e40 cm) soil layer. Soil pH, total phosphorus (TP), available phosphorus (AP), organic matter (OM), total nitrogen (TN), and hydrolyzed nitrogen (HN) were determined. A pH meter was used for soil pH. The WalkleyeBlack K2Cr2O7eH2SO4 wet oxidation method was used to measure soil organic matter Total nitrogen was measured using the Kjeldahl method (Justine et al., 2015) and also a diffusion method (Lal and Shukla, 2004). Hydrolyzed nitrogen was measured using a diffusion method (Lal and Shukla, 2004). Total phosphorus was measured using HClO4eH2SO4 colorimetry, and available phosphorus was determined using acid solution-molybdenum antimony resistance. For soil physical properties, intact soil cores were collected at nine random points in each plot and each soil layer using a steel cylinder corer with a 100-cm3 volume. Water holding capacity, maximum water holding capacity, capillary water holding capacity, minimum water holding capacity, soil density, non-capillary porosity, capillary porosity, and total porosity were measured (Chen and Cao, 2014; Cheng et al., 2017; Justine et al., 2015). 2.4. Data analysis We calculated plant species diversity, species richness, and Simpson, ShannoneWiener, and Pielou indices, along the vertical layering of vegetation as the sum of the number of species found in each survey unit at high, medium, and low stand density plantations. The representativeness of the species richness obtained in the field was evaluated by comparing different estimators of richness using PRIMER version 7 (Clarke and Gorley, 2015). Differences in herb and shrub species community structure were tested among the three stand densities using a permutation multivariate analysis of variance (PERMANOVA). This analysis was based on a zero-adjusted BrayeCurtis similarity matrix, type III partial sums of squares, and 9999 random permutations of the residuals under the reduced model (Anderson et al., 2008). An ecological heatmap was produced with both herb and shrub species grouped together in the three stand densities. To explore species distribution across densities, we used a principal coordinate analysis (PCoA), an unconstrained ordination of multivariate data, with the BrayeCurtis resemblance measure of species abundance data (Anderson and Willis, 2003). In the PCoA, arrow vector orientation and length represent the association, direction, and strength between traits and the ordination axis. All analyses were conducted in PRIMER version 7 and PERMANOVA add-on software (Anderson and Willis, 2003; Clarke and Gorley, 2015). To determine the degree of association between shrub and herb species with stand density, we built heat maps (Somer and Clarke, 2013) in which plots at high, medium, or low density were classified based on a BrayeCurtis similarity index, and the species were classified based upon Whittaker's index of association Whittaker's index of association (1952). ANOVAs were used to determine the relationship between the three density levels and the soil chemical and physical properties within three layers of soil depth. Principal component analysis (PCA) was used to evaluate the overall differences in planting density at 0e40 cm soil depth, and both PCA and redundancy analysis (RDA) using Monte Carlo permutation (999 repetitions) were used to test the relationships among the soil physical and chemical properties. SPSS version 20 (Chicago, USA) was used to statistically analyze the data and Canoco 5 was applied for RDA and PCA analysis of the data. Differences were considered significant when p < 0.05.

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Fig. 2. Frequency distribution of height and diameter at breast height (DBH) in high-density (A), medium-density (B), and low-density (C) stands within a P. massoniana stands.

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3. Results 3.1. Regeneration status of Pinus massoniana plantations The distribution of height (H) and diameter at breast height (DBH) (Fig. 2) had approximately normal distributions (p ¼ 0.01), with the exception of DBH in the LD and MD classes. A significant relationship was observed between tree density and DBH (p < 0.01); that is, as stand density decreased, DBH of P. massoniana tended to increase (Fig. 3). There was a significant difference between DBH in HD stands (13.4 ± 0.5 cm) and LD (15.6 ± 1.2 cm) and MD stands (14.9 ± 0.9 cm) (p < 0.01). Trees in the LD stands were significantly taller (13.2 ± 0.5 m) compared to trees in the MD (10.4 ± 0.1 m) and HD stands (9.3 ± 0.3 m) (Fig. 3). Tree species regeneration status showed significant differences in the demography of saplings and seedlings (Fig. 4). We recorded 35.8 ± 4.4% seedlings, 25.33 ± 2.2% saplings, and 32.32 ± 2.08% trees in LD class blocks; 29.32 ± 2.74% seedlings, 27.86 ± 2.7% saplings, and 26.79 ± 1.94% trees in MD class blocks; and 20.8 ± 1.5% seedlings, 28.46 ± 2.39% saplings, and 30.2 ± 4.27% trees in HD class blocks. The highest percentage of seedlings (35.84%) was recorded in an LD block, while the lowest percentage of seedlings (20.80%) was recorded in an HD block. The lowest sapling percentage (27.10%) was observed in the LD class, while the highest sapling percentage (28.46%) was found in the MD class. The highest percentage of trees (34.02%) was observed in the HD class, while the lowest percentage of trees (26.79%) was recorded in the MD class (Fig. 4). The highest density of regenerating species was recorded for P. massoniana (0.31), Pistacia chinensis (0.21), and Cunninghamia lanceolata (0.22) in LD stands. In MD and HD stands, similar species were observed in lower abundance. In HD

Fig. 3. Distribution of height and DBH across the three different stand densities in the study area, where bars represent one standard deviation.

Fig. 4. Mean percentage of seedlings, saplings, and trees encountered during field data collection in the three stand density treatments. Error bars represent one standard deviation.

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Table 1 Regeneration status of different trees species in the three different density classes of mature Pinus massoniana plantation. Species

Low Density

Pinus massoniana Quercus glandulifera Ilex purpurea Pistacia chinensis Cunninghamia lanceolata Cinnamomum camphora Koelreuteria paniculata Diospyros lotus Albizia julibrissin Sapium sebiferum Melia azedarach Zanthoxylum ailanthoides Pinus massoniana Quercus glandulifera Ilex purpurea Pistacia chinensis Cunninghamia lanceolata Cinnamomum camphora Koelreuteria paniculata Diospyros lotus Albizia julibrissin Sapium sebiferum Pinus massoniana Quercus glandulifera Ilex purpurea Pistacia chinensis Cunninghamia lanceolata Cinnamomum camphora Diospyros lotus Albizia julibrissin Melia azedarach

D (ind.m2)

RD (%)

F (%)

RF (%)

Ab (%)

RA (%)

IV

0.31 0.18 0.19 0.21 0.22 0.15 0.13 0.13 0.11 0.14 0.16 0.18 Medium Density 0.22 0.14 0.16 0.17 0.2 0.13 0.1 0.09 0.08 0.1 High Density 0.12 0.08 0.08 0.11 0.13 0.07 0.06 0.04 0.08

1.81 1.33 1.39 1.47 1.51 1.28 1.22 1.23 1.13 1.23 1.42 1.31

22 13 16 15 18 13 11 9 7 11 7 9

3.1 2.08 2.06 2.11 2.44 1.96 1.88 1.91 1.72 1.79 1.85 1.98

1.43 1.35 1.38 1.4 1.41 1.28 1.19 1.17 1.15 1.14 1.16 1.29

2.35 2.23 2.06 2.12 2.46 2.49 2.1 2.22 2.11 2.07 2.14 2.16

7.26 5.64 5.51 5.7 6.41 5.73 5.2 5.36 4.96 5.09 5.41 5.45

1.54 1.23 1.18 1.32 1.25 1.06 0.92 1.13 0.94 1.1

17 12 11 9 15 11 8 7 4 6

2.85 1.98 1.88 1.85 2.25 1.54 1.53 1.62 1.49 1.44

1.25 1.01 1.12 1.02 1.11 0.96 0.95 1.11 0.92 0.95

1.86 1.78 1.82 1.96 2.15 2.2 1.8 1.75 1.84 1.95

6.25 4.99 4.88 5.13 5.65 4.8 4.25 4.5 4.27 4.49

0.86 0.89 0.92 0.81 1.01 0.76 0.57 0.61 0.49

15 10 8 11 13 14 8 10 11

1.54 1.2 1.01 1.06 1.52 1.25 1.13 0.96 1.28

0.85 0.91 0.89 0.87 0.96 0.78 0.92 0.71 0.97

1.05 1.1 1.13 1.21 1.39 1.33 1.14 1.16 1.2

3.45 3.19 3.06 3.08 3.92 3.34 2.84 2.73 2.97

D ¼ Density; RD ¼ Relative Density; F ¼ Frequency, RF ¼ Relative Frequency; Ab ¼ Abundance, RA ¼ Relative Abundance; IV ¼ Importance Value, ind.m2 ¼ individuals per square meter.

stands, the greatest frequency of occurrence was calculated for Pinus massoniana (22%), C. lanceolata (18%), and Ilex purpurea (19%), while in the other two density types, P. massoniana (17%), C. lanceolata (15%) and Quercus glandulifera (12%) were the most frequently recorded species. In LD stands, P. massoniana had the highest importance value (IV) (7.25), followed by C. lanceolata (6.41), and Cinnamomum camphora (5.73). In MD stands, P. massoniana had the highest IV (6.25), followed by Cunninghamia lanceolata (5.65), Pistacia chinensis (5.13), Q. glandulifera (4.99), and Cinnamomum camphora (4.8). In HD stands, Cunninghamia lanceolata had the highest IV (3.92), followed by Pinus massoniana (3.41) and Cinnamomum camphora (3.3) (Table 1). In summary, regeneration of the same tree species was observed in stands of all three densities; however, regeneration was negatively correlated with increasing tree density. All studied sites were generally regenerating well, but MD stands had the highest number of seedlings (37,600 ha1) and saplings (19,560 ha1), followed by LD stands (35,200 seedlings ha1 and 17,600 saplings ha1) (Table 1). 3.2. Understory species richness and sample completeness Sample-based rarefaction curves for herbaceous species indicated a total species richness of 42, ranging from 27 to 38 species per block depending on density (Table 2). The completeness of the inventory for HD and MD blocks varied from 95% to 100%. For LD stands, completeness varied from 76% to 100%; those low values are due to the estimated number of species

Table 2 Species richness and diversity of herbaceous and shrub species at the three planting densities in the Taizishan Forestry Administration Bureau. Stand

LD MD HD

Herb Layer

Shrub Layer

Richness

Simpson Index

Shannon Index

Pielou Index

Richness

Simpson Index

Shannon Index

Pielou Index

38.7 ± 3.7a 35.6 ± 1.5a 27.6 ± 3.1a

0.81 ± 0.07a 0.79 ± 0.1a 0.74 ± 0.08a

2.59 ± 00.4a 2.45 ± 0.1a 2.19 ± 0.01a

0.84 ± 0.09a 0.85 ± 0.07a 0.83 ± 0.05a

30.7 ± 2.8a 29.3 ± 1.1a 25.6 ± 3.2a

0.75 ± 0.08a 0.66 ± 0.02a 0.64 ± 0.06a

2.587 ± 0.4a 2.208 ± 0.01a 2.31 ± 0.05b

0.8 ± 0.05a 0.84 ± 0.01a 0.67 ± 0.03b

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Fig. 5. Extrapolation indices used for small plots of data to predict herbaceous species accumulation.

based on Jacknife 2 estimation (Fig. 5). These results confirm adequate sampling effort of the inventory in the three stand densities. Similarly, for shrub species, total species richness was 30 for LD, and varied from 25 to 30 species depending on density (Table 2). The completeness of inventory in HD stands varied from 84% to 100%, and in LD stands it varied from 76% to 100%. The lower limits of the ranges were the estimated number of species based upon Jacknife 1 and 2 estimation for MD stands (Fig. 6). As for herbaceous species, these results confirm adequate sampling efforts for all the three stand densities. 3.3. Understory community structure in different plantation density management The understory of the studied sites was composed of 108 genera, including both herbs and shrubs. The herb community structure differed based on stand density (pseudo F ¼ 4.1; p-perm ¼ 0.0001). The herb community composition in HD stands was different to that in MD stands (Student's t ¼ 2.3; p-perm ¼ 0.0001; 49.4% of average similarity between plots/within density) and LD stands (Student's t ¼ 2.25; p-perm ¼ 0.0001; 52% of average similarity between plots/within density); there were no statistically significant differences between LD and MD stands. PCoA 1 for herb species showed 21.8% variation, while

Fig. 6. Extrapolation indices used for small plots of data to predict shrub species accumulation.

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Fig. 7. PCoA analysis of the herb species in the three stand densities of Pinus massoniana plantations.

Fig. 8. PCoA analysis of the shrub species in the three stand densities of Pinus massoniana plantation.

PCoA 2 describes 17.7% variation (Fig. 7). Vitis amurensis was the most represented species in LD blocks, while MD blocks were dominated by Carex duriuscula. Imperata cylindrica and Aristolochia mollissima were abundant in HD blocks (Fig. 7). Shrub composition also differed depending on stand density (pseudo F ¼ 4.58; p-perm ¼ 0.0001). Shrub composition in HD stands differed from that in MD stands (Student's t ¼ 2.18; p-perm ¼ 0.0001; 40.5% of average similarity between plots/within density) and LD stands (Student's t ¼ 2.72; p-perm ¼ 0.0001; 36% of average similarity between transects/within density); there were no statistically significant differences between LD and MD stands (Student's t ¼ 1.39; p-perm ¼ 0.061; 41.1% of average similarity between transects/within density). In the PCoA of shrub species distribution (Fig. 8), the first two coordinates explained 42.4% of the variation. The first axis best separated species of HD stands (such as Wisteria sinensis and Glochidion puberum) from species of LD stands (such as Symplocos sumuntia, Rosa cymosa, and R. Laevigata). Meanwhile, axis 2 better separated species of HD stand from species of MD stands (such as Lindera glauca) (Fig. 8).

3.4. Shrub and herb species association to density LD and MD plots were classified into two groups based on shrub community structure, while HD plots were classified into two different groups (Supplementary Fig. S1). Shrubs Euscaphis japonica, Ligustrum quihoui, Broussonetia papyrifera, Vitex negundo, Mallotus apelta, Rhus chinensis, Cudrania tricuspidata, Rosa laevigata, R. cymosa, and Lindera glauca represented the more common species along the density gradient (Supplementary S1). In general, the abundance of shrubs was higher in HD blocks than in LD or MD blocks. Furthermore, we observed that the group of B. papyrifera, V. negundo, M. apelta, Rhus laevigata, Rosa cymosa, L. glauca, and S. sumuntia were more abundant compared to other shrubs. This group also followed the same general pattern of greater abundance in HD blocks compared to MD or LD blocks.

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Based on shrub community structure, LD and MD plots tended to group together more than HD plots, with more even distribution along the classification gradient (Supplementary Fig. S2). On the other hand, shrub species associations exhibited more than ten groups, from which the group containing Rubus corchorifolius, Aristolochia mollissima, and I. cylindrica, and the group containing Carex spp. represented the most common species along the density gradient. 3.5. Stand density and change in soil physicochemical properties Soils of all stand densities were acidic, mainly due to strong leaching. This trend increased with stand density and soil depth (Table 3). Similarly, at all soil depths, the amount of soil organic matter fluctuated, decreasing in the soils from MD stands and increasing in the soils from HD stands. A similar trend was observed for total nitrogen and hydrolyzed nitrogen in all soil layers (Table 3). For the amount of total and available phosphorus, we found no clear trends. Soils from MD stands showed the highest maximum water holding capacity, which gradually decreased with soil depth. The capillary water holding capacity in MD areas was highest in the third soil layer. However, the minimum water holding capacity showed its highest values in HD stands. Soil density was relatively constant across all stand densities but showed a slight increasing trend as soil depth increased. Non-capillary porosity was more in the HD and MD in the second layer of soil while capillary porosity was more in the third soil layer in the MD Total porosity is more in MD in the third soil layer compared with that of second and first soil layer (Table 4). 3.6. Relationship between soil physical and chemical properties We found significant correlations between soil physical and chemical properties (Fig. 10). The redundancy analysis indicated a strong positive relationship for the minimum and maximum water holding capacity, and non-capillary porosity with all soil chemical properties. However, the other physical properties (capillary tube water holding capacity, soil density, capillary porosity, and total porosity) were significantly negatively correlated with chemical properties. Organic matter and total nitrogen increased with increases in minimum and maximum water holding capacity and non-capillary porosity. A PCA

Table 3 Soil chemical characteristics in different stand densities of Pinus massoniana plantations. Density Class

Soil Properties OM (%)

TN (mg kg-1)

HN (mg kg-1)

TP (g kg-1)

AP (mg kg-1)

pH

2.04 ± 0.08a 0.72 ± 0.01a 1.18 ± 0.07a

227.9 ± 12.05a 45.97 ± 8.12a 71.87 ± 11.53a

6.35 ± 0.1a 4.14 ± 0.08a 4.18 ± 0.06a

7.74 ± 0.1a 5.97 ± 0.08a 5.5 ± 0.02a

4.44 ± 0.04 5.32 ± 0.07 5.53 ± 0.03

0.55 ± 0.02a 0.42 ± 0.01a 0.71 ± 0.06a

84.97 ± 13.02a 24.8 ± 6.85a 76.7 ± 9.65a

3.84 ± 0.17a 4.16 ± 0.01a 4.24 ± 0.1a

3.93 ± 0.05a 6.51 ± 0.07a 5.6 ± 0.02a

4.72 ± 0.1 5.54 ± 0.04 5.74 ± 0.07

0.5 ± 0.02a 0.38 ± 0.02a 0.54 ± a

16.77 ± 4.55a 16.97 ± 4.44a 16.77 ± 5.22a

3.33 ± 0.0a 3.63 ± 0.0a 4.23 ± 0.0a

7.4 ± 0.2a 5.24 ± 0.1a 3.6 ± 0.08a

4.86 ± 0.05 5.76 ± 0.02 5.65 ± 0.04

First Layer (0e10 cm) LD 7.15 ± 0.06d MD 3.48 ± 0.03bc HD 5.85 ± 0.04a Second Layer (10e20 cm) LD 2.71 ± 0.03d MD 2.07 ± 0.04bc HD 3.43 ± 0.02a Third Layer (20e40 cm) LD 2.55 ± 0.01b MD 1.83 ± 0.04cd HD 2.67 ± 0.05a

OM ¼ organic matter, TN ¼ total nitrogen, HN ¼ hydrolyzed nitrogen, TP ¼ total phosphorus, AP ¼ available phosphorus. Lowercase letters indicate significant differences among the means.

Table 4 Soil physical properties at three soil depths recorded in the three stand densities of Pinus massoniana stands. MXWHC (g kg1)

CWHC (g kg1)

MNWHC (g kg1)

SD (g cm3)

NCP (%)

CP (%)

TP (%)

159.89 ± 11.9a 161.47 ± 10.3a 168.37 ± 32.6a

114.73 ± 26.9a 105.39 ± 7.7a 127.28 ± 34.8a

1.08 ± 0.11b 1.09 ± 0.13 ab 1.06 ± 0.12a

5.40 ± 0.6a 6.78 ± 0.9a 6.13 ± 2.4a

17.30 ± 1.7b 17.22 ± 0.99 ab 17.56 ± 1.4a

22.60 ± 2.2b 24.19 ± 0.0a 23.69 ± 1.7a

166.80 ± 26.2a 153.81 ± 3.2a 148.06 ± 14.3a

121.51 ± 37.9a 96.26 ± 1.2a 114.31 ± 13.7a

1.20 ± 0.07a 1.21 ± 0.02a 1.16 ± 0.09a

5.43 ± 1.4a 6.68 ± 0.7a 7.40 ± 0.5a

18.50 ± 2.8 ab 18.59 ± 0.19a 17.06 ± 0.4a

25.41 ± 2.3a 25.36 ± 0.6a 24.46 ± 0.3a

157.15 ± 15.8a 176.27 ± 14.06a 154.44 ± 12.8a

106.6 ± 11.9 ab 88.69 ± 8.6a 120.16 ± 23.1b

1.20 ± 0.13a 1.29 ± 0.06a 1.22 ± 0.09a

6.05 ± 0.3a 3.12 ± 0.3a 6.27 ± 1.5a

20.01 ± 0.18a 22.57 ± 1.5a 18.70 ± 0.17a

24.82 ± 0.2a 25.53 ± 0.3a 24.97 ± 1.7a

First Layer (0e10 cm) LD 210.45 ± 14.2a MD 226.93 ± 27.1a HD 225.04 ± 18.2a Second Layer (10e20 cm) LD 212.95 ± 27.8a MD 210.29 ± 2.4a HD 212.14 ± 18.2a Third Layer (20e40 cm) LD 207.93 ± 22.3a MD 198.13 ± 3.2a HD 206.38 ± 25.1a

MXWHC ¼ maximum water holding capacity, CWHC ¼ capillary water holding capacity, MNWHC ¼ minimum water holding capacity, SD ¼ soil density, NCP ¼ non-capillary porosity, CP ¼ capillary porosity, TP ¼ total porosity.

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Fig. 9. Principal component analysis (PCA) of soil physical properties. MXWHC ¼ maximum water holding capacity, CWHC ¼ capillary water holding capacity, MNWHC ¼ minimum water holding capacity, SD ¼ soil density, NCP: non-capillary porosity, CP: capillary porosity, LD ¼ low planting density, MD ¼ medium planting density, HD ¼ high planting density.

Fig. 10. Ordination plot of redundancy analysis showing relationships between soil physical properties. MXWHC ¼ maximum water holding capacity, CWHC ¼ capillary water holding capacity, MNWHC ¼ minimum water holding capacity, SD ¼ soil density, NCP ¼ non-capillary porosity.

indicated clear differences in the soil physical and chemical properties among the different planting densities (Fig. 9). All variables were clearly clustered into three well-differentiated groups representing each density treatment. The cumulative variance of contributions reached 86.2%, where PC1 explained 85.6% and PC2 explained 0.60% of variance, over the average of three soil layers. Overall, this analysis indicates that soil physical and chemical properties were strongly affected by the decrease in stand density (Fig. 10).

4. Discussion Patterns of diversity and species composition represent fundamental concepts in the conservation of natural resources, and are frequent targets of ecological studies (Barbier et al., 2008; Langer et al., 2008). Knowledge of floristic composition is essential for understanding the overall structure and function of ecosystems (Bermúdez et al., 2007). Quantitative analyses of diversity, regeneration status of tree species, and soil physicochemical investigation may provide baseline information for formulating management and conservation strategies for both natural areas and forest plantations, such as in this research.

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4.1. Regeneration of trees and stand density management Recently, an intense debate has begun as to whether large-scale plantations are capable of creating self-sustaining forest ecosystems through succession. Forest management considerations such as tree species selection, tree density and age, light environment, thinning, rotation, and site preparation are among the main factors affecting forest composition and structure, ecosystem function, and species diversity in managed forests (Sharma et al., 2016). We examined how tree growth, understory plants, tree regeneration, and soil physicochemical properties are affected by changes in stand density in a P. massoniana plantation in central China. Space availability in the forest is regarded as an important factor for stand vigor and tree growth, bert et al., 2016). We found that DBH of HD and stand density is, therefore, expected to have a significant effect on DBH (He plantations was significantly lower than in lower density classes, but no significant difference was observed between MD and LD stands. Similar results were reported by Chen and Cao (2014) for other coniferous tree species such as Pinus tabuliformis. Furthermore, an increase in tree growth might decline with time, resulting in a constricted canopy and signifying the potential influence of density management (Soucy et al., 2012). The normal distributions of height and DBH of P. massoniana in most of the study sites indicate that the local climate is suitable for the species (Fig. 2). Forest regeneration is an indicator of the overall health of forest ecosystem (Abe et al., 2008), and is considered a vital process in which old trees are replaced by young ones (Singh et al., 2016). In natural vegetation restoration, seedlings are an important and crucial stage of plant life. Variables such as planting density, species composition, and site quality affect the performance and regeneration of plantations (Sansevero et al., 2017, 2011). Various age groups of species determine the reproductive population and the future development of forest ecosystem (Sharma et al., 2016; Soucy et al., 2012). The presence of sufficient number of young trees, seedling, and saplings ensures good or satisfactory regeneration potential, while inadequate numbers predict poor regeneration (Saxena and Singh, 1998). Our results indicated that both seedling and sapling density fell when stand density increased, possibly due to the closed canopies (Chen and Cao, 2014). Meanwhile, at low and medium densities, the overall regeneration status of the plantation appeared healthier than at high density. Other studies have also suggested that open canopies are more favorable for seed establishment and germination (Rahman et al., 2011). Nonetheless, we observed that regeneration of P. massoniana was limited in these stands, which may have been due to low/ uncertain seed supply or unfavorable microsites affecting early seed establishment and survival (Singh et al., 2016). 4.2. Impact of stand density on the forest understory vegetation Understory plant species are an important part of a stable forest ecosystem and support important ecosystem functions, and it is important to define suitable planting densities to support their growth and development (Lu et al., 2010). Studies have shown that stand density and canopy structure affect both the understory environment and vegetation growth (Lu et al., 2007). However, little information is available regarding the understory in P. massoniana plantations. Species diversity is considered to be a function of the relative distribution of the individuals among species in an area. Various long-term factors are involved in regulating species diversity, including community stability and evolutionary time, since heterogeneity of the macro- and microclimate commonly affects diversification among different plant communities. The shrub layer, which serves as to protect against soil degradation and erosion, has been shown to be negatively correlated with the height and basal area €ki et al., 2012). Still, in the current study, we observed a mean shrub cover between of dominant trees (Coll et al., 2011; Selkima 10 and 20%, with no significant differences among the three stand densities. The understory species diversity and richness was low compared to other studies, e.g., Langer et al. (2008) for P. radiata, and for P. sylvestris (Czerepko, 2018). This may be caused by the successive decline of species diversity that occurs as the canopy closes (Soucy et al., 2012). Total species richness was higher for herbaceous species than for shrubs, but those two groups exhibited the same pattern of decreasing species richness with increasing stand density. The herb layer is somewhat less responsive to canopy closure compared to the shrub layer (Wilson and Puettmann, 2007). The plantation becomes more complex over time, favoring closed forest species (Paillet et al., 2010). P. massoniana plantations with low density showed species diversity similar to natural forests described by Wang et al. (2012). This may be explained by the amount of sunlight reaching the ground in such stands being similar to the natural forests, supporting the growth of understory plants. In our study, herb and shrub species composition, richness, diversity, and structure were similar between LD and MD stands. Meanwhile, HD stands failed to develop stable understory vegetation, potentially due to low light availability as previously discussed (Kaeser et al., 2008), or to disturbances caused by extensive mushroom production or a large centipede Scolopendra subspinipes, both of which are of high economic value (Lu et al., 2010). Species composition and distribution were both negatively affected by plantation density; the lower levels of light in the high density stands could favor shade-loving plants in the understory (Putten et al., 2013). It would be interesting to expand the present research into a different environmental set-up for developing more precise and detailed understanding of ecological restoration in P. massoniana. 4.3. Effect of stand density on soil physicochemical properties Some of the most important aspects of forest restoration include the availability of soil nutrients and organic matter (Xu et al., 2018), which are the main environmental factors influencing the structure and diversity of forest plant communities (Archer et al., 2007; Sitzia et al., 2012). Soil nutrient capacity is an important determinant of growth, structure, and distri~ uelas, 2004). The diversity of the understory species in bution of plant communities (Henkin et al., 1998; Sardans and Pen

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different stand densities is often similar when soil nutrients are consistent (Chen and Cao, 2014). In our research, we found significant relationships between soil physical and chemical properties, similar to those reported by Matias et al. (2010). An increase in water availability increases plant productivity, yielding more litter of higher nutritional quality (Dirks et al., 2010). In our study, the medium density stands showed the best water-holding capacity. Still, in coniferous forests, falling needles can remain on the forest floor for long periods and result in slow decomposition, which may ultimately lower nutrient uptake by trees. Meanwhile, withered pine needles also block other plant litter decomposition and absorption by soil (Xue et al., 2014). Here, soil organic matter and phosphorus fluctuated with changes in plantation density, with greater organic matter and phosphorus contents found in LD and HD stands compared to MD stands. This variation may be due to the impacts of stand structure as reported by Wei et al. (2018). 5. Conclusions P. massoniana is a relatively understudied pine species among the pine family and different aspects of this species are still unknown at global scale. Large-scale plantations of P. massoniana in the Taizishan Mountains effectively conserve soil and water, controlling runoff, soil erosion, and contribute to carbon sequestration. Results of species accumulation curves showed that species heterogeneity was highest in low-density plantations, while medium-density stands supported high shrub species heterogeneity. Changes in community structure and composition were the most pronounced in the high-density stands. As for the community structure, both herb and shrub communities of lower densities were markedly more clustered compared to the communities of the high-density plantation. Planting in lower densities had a significant effect on the regeneration status of the understory plant species and both chemical and physical soil properties. The results of our study suggest that species conservation and ecosystem function is better supported by lower density management strategies. We believe the data presented in this study are useful in addressing conservation of the understory species diversity, and also provide a baseline for studying community ecology of P. massoniana plantations. Still, further research is necessary to account for the potential of P. massoniana plantations for biodiversity conservation, as well as timber and seed production to promote sustainable forest management and important ecosystem services. Acknowledgments We express our deepest gratitude to Taizishan Forestry Administration Bureau of Hubei province for providing support and permission to conduct this research. The authors sincerely acknowledge the efforts of Xin Huang, Kuirong Zheng, and other colleagues for their assistance in data collection. We are grateful to Dr Yongjian Wang and Dr. Wei He for technical inputs on the manuscript. Appendix A. Supplementary data Supplementary data to this article can be found online at https://doi.org/10.1016/j.gecco.2019.e00775. Funding This work was sponsored by the National Key R&D Program of China (Grant number 2017YFC0505603, 2016YFD0600201), the Major Scientific and Technical Innovation Project of Hubei Province (Grant number 2018ABA074) and the Long-term Track Research Program of Forest Ecological Station in Three Gorges Reservoir Region (Zigui) of the Yangtze River, China. We are thankful to the funding agencies for providing funds for this research. Conflicts of interest The authors report no potential conflict of interest. References Abe, M., Honda, A., Hoshizaki, K., Miguchi, H., 2008. 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