Advertisement
Browse Subject Areas
?

Click through the PLOS taxonomy to find articles in your field.

For more information about PLOS Subject Areas, click here.

  • Loading metrics

Site conditions for regeneration of climax species, the key for restoring moist deciduous tropical forest in Southern Vietnam

  • Ha T. T. Do ,

    Roles Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Project administration, Visualization, Writing – original draft, Writing – review & editing

    t.do.16@student.scu.edu.au

    Affiliations Forest Research Centre, Southern Cross University, Australia, Silviculture Research Institute, Vietnam Academy of Forest Sciences, Ha Noi, Vietnam

  • John C. Grant,

    Roles Conceptualization, Methodology, Supervision, Writing – original draft, Writing – review & editing

    Affiliation Forest Research Centre, Southern Cross University, Australia

  • Heidi C. Zimmer,

    Roles Conceptualization, Methodology, Supervision, Writing – original draft, Writing – review & editing

    Affiliation Forest Research Centre, Southern Cross University, Australia

  • Bon N. Trinh,

    Roles Investigation, Resources, Supervision

    Affiliation Silviculture Research Institute, Vietnam Academy of Forest Sciences, Ha Noi, Vietnam

  • J. Doland Nichols

    Roles Conceptualization, Funding acquisition, Methodology, Supervision, Writing – original draft, Writing – review & editing

    Affiliation Forest Research Centre, Southern Cross University, Australia

Site conditions for regeneration of climax species, the key for restoring moist deciduous tropical forest in Southern Vietnam

  • Ha T. T. Do, 
  • John C. Grant, 
  • Heidi C. Zimmer, 
  • Bon N. Trinh, 
  • J. Doland Nichols
PLOS
x

Abstract

Understanding the requirements and tolerances of the seedlings of climax species is fundamental for tropical forest restoration. This study investigates how the presence and abundance of seedlings of a previously dominant, now threatened species (Dipterocapus dyeri Pierre), varies across a range of environmental conditions. Dipterocapus dyeri seedling abundance and site characteristics were recorded at 122 observation points (4 m2) at nine clusters from two sites. Seedling presence (p = 0.065) and abundance varied significantly (p = 0.001) between the two sites, and was strongly correlated with adult D. dyeri dominance and lower soil pH, and weakly correlated with canopy openness and total stand basal area. Dipterocarpus dyeri seedlings were also grown in shade houses with three light levels on two soils. Seedling survival was significantly lower at the lowest light level (<10% full irradiance) at 13% for the forest soil and 25% for degraded soil. At higher irradiance the seedling survival rates were greater than 99%. Moisture levels remained high at the lowest light level and many seedlings died from fungal infection. We concluded that secondary forests which contain adequate numbers of adult D. dyeri as seed sources, light availability, soil pH of < 5.0, and good drainage strongly favour survival and growth of D. dyeri seedlings. Historically, D. dyeri was dominant in moist deciduous tropical forest across south-eastern Vietnam, but today it is rare. Active management of these recovering forests is essential in order to recover this high-value, climax forest species.

1. Introduction

Water, nutrients and light are key elements in plant growth and survival. These resources vary spatially, often with topographic gradients, and temporally, including as they interact with vegetation development. Water and nutrient availability in the soil is largely driven by landscape-scale factors, such as topography, substrate and climate [1,2]. Light availability on the forest floor is largely determined by the density of the forest canopy (i.e., local-scale factors), which changes through time as the forest develops [3,4]. Competition for light is a major influence on recruitment in old-growth tropical forest [5]. However, in secondary tropical forest, competition for water is more important than competition for light and drought tolerance is critical for survival [68]. This is because there is often more light reaching the forest floor, due to gaps in the canopy. Gap size directly influences light availability at the soil surface, which not only affects the germination and growth of plants in the understory, but also leads to changes in underground processes, potentially influencing soil temperature, water and tree root competition [9]–higher light and temperature at the soil surface increasing the likelihood of drought [10]. For example, single tree fall gaps can expose high-nutrient soil ideal for germination [11,12].

The mosaic distribution patterns of tree populations and tree ages in tropical forests are the results of species-specific and tree age-specific adaptations to the spatial distributions of water and nutrients [1316]. Soil type, topography and vegetation structure interact to influence seedling establishment spatially and temporally [1719]. The structure and composition of a vegetation community are maintained temporally by species’ successful regeneration [11]. Different species have different environmental requirements and different levels of tolerance to the stresses presented by different environments/site-conditions. For example, low soil pH is tolerated by many conifer species [20]. The optimum range for growing most pine seedlings is around 4.5 to 5.0 for sandy soils and 5.0 to 5.5 for fine-texture soils containing high levels of Mn [21]. Wollemia nobilis seedlings, for example, have an optimum soil pH of around 4.3 [22]. Wollemia nobilis, like many other conifers, thrives at light levels higher than typically occurs in most rainforest understories. In contrast, many broadleaf tropical species seedlings such as Neolitsea obtusifolia, Hopea odorata and Brosimum alicastrum survive better under conditions those low light levels [2326]. In order for recruitment to be successful, seeds need to fall where light and soil moisture conditions are favourable for germination and growth [6,27]. In some cases, the original conditions that have led to occupation by a specific vegetation may change to be no longer suitable for its regeneration. The regeneration of a species in tropical forest can therefore be discontinuous, with not all life stages of all species present. Mimicking these natural processes, close-to-natural silviculture techniques and nurse crop establishment were used commonly in the tropical areas as the foundational practise for middle- or late-successional afforestation during their seedling and sapling periods. Then light liberation is applied as seedling increase in height, depending on specific species light requirements [2831].

The key to regeneration may be related to the availability of appropriate microsites i.e., small-scale variation in resources and species-specific effects [32,33]. When forest stand structure influences the distribution of water, nutrient and light at the local scales, the species composition showed local ecological intra and inter species effects provided a strong influence on seedling growth [32]. Conspecific density (also known as congeneric) affects not only seed availability [3436], but also physically and biologically affects seed germination, survival and growth of seedlings through negative-density dependence mechanisms [3739]. Negative-density dependence mechanisms were shown to strongly negatively influence same species in monoculture plantation [37,40,41]. In mixed species natural forests, negative-density dependence trends (from positive to negative) with strength of the negative-density dependence mechanism on specific-species recruitment strongly depended on the quality and quantity of adult trees in the site (i.e., density, distribution and size of remnant trees).

Dipterocarpaceae was previously abundant throughout southeast Asia, however most remaining forests are heavily disturbed and are dominated by deciduous tree species and bamboo [4244]. Dipterocarp species are known to be strongly associated with specific soil and light conditions, especially as seedlings. Microsite light availability, determined by gap size, is likely to be the most influential factor in natural regeneration of dipterocarps, as dipterocarp species’ light requirements change with life stage. They prefer shade for germination, partial light during seedling and sapling stages, and full light as mature trees [4547]. The effect of light availability appears to be stronger than the effect of foliar herbivory on Dipterocarp seedling survival and growth [48,49]. Understanding patterns of natural regeneration of dipterocarps will contribute to efforts to restore and re-establish this highly valued and important type of forest [5052].

Dipterocarpus dyeri is native to Myanmar, Thailand, Viet Nam, Cambodia and Peninsular Malaysia. The species has been globally assessed as Endangered in the IUCN Red list [53,54]. Most dipterocarp species, including Dipterocarpus dyeri Pierre, are high value timber species, and as such, have been selectively logged across South-east Asia [42]. Dipterocarpus dyeri has been targeted in particular because of its high density wood (~ 0.8 g/cm3) and also their resins (dammar) which can be extracted for caulking boats, varnish paint, and medicine [42,5457]. Dipterocarpus dyeri today is one of the rarest species in the forest and there is limited information on species ecology regeneration and growing site conditions [54,58].

Seedling recruitment is a crucial process in long term forest dynamics. An accurate understanding of tree recruitment patterns in forest stands and microhabitats is required to predict forest development and optimise forest management to achieve ecological and/or production goals [5961]. This study aimed to determine the primary ecological processes driving Dipterocarpus dyeri seedling establishment and survival. The micro-scale conditions belong to three main groups: (1) soil, including particle size distribution and chemical properties and encompassed in soil type; (2) site, including topographic wetness; and (3) forest stand characteristics, including canopy openness, basal area, species biodiversity and dominance of adult D. dyeri. Determining the requirements for D. dyeri seedlings will improve understanding of secondary forest regeneration. This will help land managers to choose suitable sites to manage regeneration, prepare and plant nursery stock, and develop appropriate silviculture techniques for restoration of dipterocarp forests in southeast Vietnam.

2. Methods

2.1. Study sites

The study was conducted in a monsoonal evergreen broad-leaved forest in the Dong Nai Biosphere Reserve (DNBR), Dong Nai Province, Vietnam (Fig 1; the maps were sourced from Natural Earth [62]), which are licensed under a CC BY-SA 4.0.). The Director of DNBR Dr. Tran Van Mui, gave permission to conduct this research project in DNBR. The Reserve extends between 11°20’50”N– 11°50’20”N and 107°09’05”E– 107°35’20”E [63]. The area is in the lowland monsoon tropical climate zone with mean annual rainfall of 1,850 mm of which 80% falls in the wet season (from April to October). The mean annual temperature is approximately 26°C, with small seasonal fluctuations [64].

thumbnail
Fig 1. Location of study site and plots in Dong Nai Province, Vietnam.

Colours on the basemap represent forested (green) and unforested (yellow and brown) land cover. The land cover basemap, country and province borders were sourced from NaturalEarth (http://www.naturalearthdata.com/about/terms-of-use/).

https://doi.org/10.1371/journal.pone.0233524.g001

Two study sites were established with elevations that ranged from 44 to 130 m asl. A mixed-bamboo (MB) site (UTM 48N 736532E 1257916N (Plot SK3); > 100 m elevation), at Phu Ly Commune was in a steep landscape (10-20°) and a mixed-evergreen (ME) site (UTM 48N 716275E 1236117N (Plot DD2); 70–95 m elevation) occurred on gentle slopes.

The soils at both sites were classified as Acrisols (grey podzolic soils) [65]. The ME site soils are mapped as Chromic Acrisols (Fp), developed on old alluvium. These soils are yellowish brown and clayey throughout with a Bts horizon at 30–100 cm depth. The MB site soils are Endolithic Chromic Acrisols (Fs), which had developed on schist and shales [65]. The soils in this site are shallow (50–70 cm), yellowish brown sandy clay loam to light clay textures and a BCts horizon at 30–40 cm above R or C horizons. The soil chemical analysis (S1 Table) showed a high level of base saturation (more than 50%), indicating both soils might be better classified as Luvisols [66].

The forests in the study area are lowland tropical forests dominated by dipterocarp and Lagerstroemia (Lythraceae) species [6769]. Most of forests in the area are recovered after logging (early 1943 and from 1976 to 1996), herbicide spraying (1961–1971) and other deforestation activities (1976–1996) [70,71]. The forests at the ME site contained mixed evergreen tree species (D. dyeri, Hopea recopei, Vatica odorata, Artocarpus spp., Syzygium spp.) and deciduous species (Lagerstroemia spp., Cratoxylum spp., Nephelium melliferum). The MB site was dominated by bamboos which were considered as a regrowth stage of broadleaf forest after disturbances [68,69].

2.2. Study species

Dipterocarpus dyeri is a large lowland evergreen rainforest tree species. It also occurs in dry evergreen forests as a brevideciduous species, as they lose their leaves for only a few days [42,72]. In DNBR, according to our observations since 2016, fruiting of adult D. dyeri trees (DBH more than 40 cm) occurs almost every year with flowering in November–December and fruit maturation in March–April.

2.3. Data collection

The data from the forests were collected during the dry season in November 2017 –January 2018 inside the DNBR (Fig 1). A total of 122 observation points (2 m x 2 m) were taken from 18 sampling clusters (represented by plot vegetation data, Table 1, Fig 1, S1 Data). The locations of these clusters and points were allocated on two sites with 101 points (15 plots) on Mixed Evergreen (ME), and 21 points (3 clusters) on Mixed Bamboo (MB), approximately 20 km from ME site (Fig 1). First, we identified potential D. dyeri (DBH > 40 cm) mother trees. Then a search for D. dyeri seedlings was undertaken with distance from the mother tree 100 m. If a seedling was found, then that seedling became a corner of a 400 m2 plot. Then all seedlings within that area were identified and measured. If no seedlings were found, then a similar 400 m2 plot was established for surveying site and soil conditions, with a mother tree as the centre and five observation points (each of the four corners and at the centre of the plot).

thumbnail
Table 1. Description of soil and site characteristics from 122 observation points.

https://doi.org/10.1371/journal.pone.0233524.t001

2.3.1 Vegetation composition.

In each plot, all woody species (excluding lianas) were recorded and divided into three classes based on the diameter at 1.3 m height from the ground (DBH): adults (DBH ≥ 10 cm), juveniles (5 cm ≤ DBH < 10 cm). Adults and juveniles were surveyed from 400 m2 plots while seedlings of all species were surveyed from the observation points.

2.3.2 Soil.

At each observation point, a description of soil from 0–35 cm depth was made, including horizons, colour and texture. One topsoil (0–10 cm depth) sample which was a mixture of soil from 3–5 observation points was taken for soil chemical characterisation of each sampling cluster. At each sampling cluster one core sample (5 cm diameter x 5 cm length) was taken for topsoil bulk density calculation.

2.3.3 Light.

A hemispherical canopy photograph was taken at each observation point at 170 cm above the ground. We chose this height to avoid the shrub and herb layers. These photos were used to determine canopy openness (%) using Gap Light Analyzer (GLA) software [73], after processing the image through SideLook [74] using automatic thresholding. The procedure of using automatic threshold to adjudge colour canopy photographs is recommended for assessing canopy openness [75].

2.3.4 Environment.

Basic site conditions were described at each observation point, including slope (degrees), aspect (degrees), outcrop rock (% cover), forest floor vegetation cover (%), litter cover (%) and litter thickness (cm). Topographic wetness index (TWI) [76], was calculated as a soil moisture indicator [77,78] for each observation point was derived by Arctoolbox from a digital elevation model (DEM) through SAGAGIS, AcrGIS v 10.1. A DEM of 30 x 30 m grid spacing was downloaded from https://earthexplorer.usgs.gov/.

2.3.5 Shade house experiment establishment.

Seeds were collected from one mother tree from Cay Gui Forest Ranger Station (approximately 500 m from plot CG1). The seedlings were germinated using moist sand for 20–30 days until developing to seedlings with two true leaves (S2A Fig) which were then transplanted in plastic pots (8 cm diameter x 40 cm height). There were six treatments of three light levels (high, medium and low) and two sources of soil (old growth forest and heavily logged and degraded forest) with a total of 432 seedlings (72 seedlings per treatment). Each light treatment was set up in a shelter with light levels controlled by shade cloth, one layer for the high level, doubling for the medium level and tripling for the low level. The light levels were confirmed by the measurement of leaf area index (LAI) by using Li-2200. The LAI at the three shelters were 2.9, 5.4 and 7.1 giving estimations of canopy openness for each light levels were proximately 45%, 20% and 5% of full sun, respectively. Soil used for the trial was the topsoil of a Chromic Acrisol (Fp) and it was collected from two sites. Both soils were light clays in texture and the old growth forest soil (F) was higher in organic matter, total nitrogen and CEC than the degraded site soil (D) (S1 Table).

2.4. Data analysis

2.4.1. Forest data: Correlation between presence/number of D. dyeri seedlings and microsite conditions.

The effect of site (mixed evergreen and mixed bamboo sites) on the assemblage of seedlings of the target species per observation point was tested using multivariate models [80] through manyglm function in mvabund R package [81]. This function analyses the individual and interactive influences of each site condition variable based on mixed effect models. Negative binomial family of distribution link was chosen as seedling abundance data was overdispersed.

The sets of variables were also used to test their effects on presence and abundance of D. dyeri seedlings at observation points in generalized linear regression models (GLM). We used the glm.nb function within ‘MASS’ [82] to fit models with a negative binomial family with distribution for data collected at observation points where seedlings occurred. We also used function glm from package ‘lme4’ [83] with binomial family for presence/absence data. In the GLM, the cluster (plot) of observation point was not treated as random factor since the forest stand variables were aggregated in the cluster. The final models were selected by AIC in the stepwise search through function step in stats R package stats [79].

As canopy openness was one of the factors of most interest in the forests, we used Bayes t. test function in BayesianFirstAid R package [84] to compare the difference in canopy openness against seedling abundance level groups and between presence and absence groups for all observation points and for each site.

2.4.2. D. dyeri seedling in shade houses: Influence of soil and light.

To investigate the differences in seedling survival according to light level and soil we used the Pearson Chi-squared test. Analysis of variance (ANOVA) was used to compare the differences in seedling growth (based on diameter and height) among treatments (soil types and light levels, and their interactions).

3. Results

3.1. Forest data: Differences in seedling abundance in varying soil and site conditions

Correlations between soil and stand properties differed between the two sites (S1 Fig). Stand basal area (BA) was weakly correlated with canopy openness (CO) on the mixed evergreen (ME) site and moderately correlated with proportion of adult D. dyeri on the higher elevation mixed bamboo (MB) site. Canopy openness showed weak negative correlations with soil CN, P2O5 and sand content, and these correlations were similar on the higher site (S1 Fig). For the observation points where the seedlings were present, the correlations of site and soil properties were quite similar to the correlations at all observation points (S1 Fig).

The multivariate test of deviance indicated a significant effect of site on D. dyeri seedling abundance (p = 0.001) and no significant effect on D. dyeri presence (p = 0.065). Both the abundance and presence of D. dyeri seedlings were positively correlated with the site ME association, with coefficients (Wald value) of 2.5 and 1.98 respectively.

Seedlings were more likely to be present in darker sites (Table 2, Fig 2, S1 Fig). The association of D. dyeri seedling with lower CO was also indicated by the mean difference in CO between the presence and absence observation points of -2.1% (95% credible interval from -3.6 to -0.65) (Fig 2A). The lower CO was also found on ME site with the mean difference of CO between presence and absence points was -1.9% (95% credible interval from -3.3 to -0.48) (Fig 2B). However, the lower CO points where D. dyeri seedlings were absent on the MB site was not clear, with mean of difference with the present points was -1.1 (95% credible interval from -6.4 to 4.1) (Fig 2C). The results of the GLM also indicated that presence of seedlings significantly negatively correlated with CO on both sites (p = 0.01), and with ME site (p = 0.007), but not correlated with the MB site (Table 2).

thumbnail
Fig 2. Difference of means of canopy openness (%) between presence (μ1) and absence (μ2) of seedlings for all data (A), for points on mixed evergreen site (B) and for points on bamboo dominant site (C).

https://doi.org/10.1371/journal.pone.0233524.g002

thumbnail
Table 2. Results for four generalized linear models which predict presence and abundance of D. dyeri seedlings per observation point at both sites (models 1 and 2), and at the mixed evergreen (models 3 and 4) site only.

ME: Mixed evergreen, MB: Mixed bamboo, BA: Stand basal area, PD.A: Dominance of adult D. dyeri.

https://doi.org/10.1371/journal.pone.0233524.t002

The dominance of adult D. dyeri trees (PD.A) was positively correlated with the presence of seedlings for both sites (p = 0.006). PD.A was positively correlated with presence and abundance of seedling on ME site, but was not correlated to these variables on the MB site (Table 2). The results from BMA showed that, PD.A was the fourth most important variable in the presence of seedling model with a probability of 46% coefficient is not equal to zero, coefficient of 1.704 (± 2.218), but PD.A was the least important variable in the abundance model with only 7.4% probability that coefficient is not equal to zero, coefficient of -0.018 (± 0.176).

Seedling abundance was not correlated with CO (Table 2) but it was marginally negatively correlated with stand total basal area (BA) with p = 0.069 (Table 2, but when seedlings were present their abundance was positively correlated with stand total basal area (p = 0.0004, Table 2). The correlations of BA with seedling presence and abundance were significant on the ME site, with a negative correlation with presence, and positive correlation with abundance. However, all of the variables included in the model-averaged analysis were not always negatively or positively correlated with abundance of seedlings (S2 Table). Comparing with other factors, BA showed weaker effects to seedling presence than CO and weaker effects than soil pH to the seedling abundance (Table 2).

When analysed across both sites, seedling abundance was negatively correlated with soil pH and positively correlated with BA (Table 2). In contrast, when the data for the ME site was analysed separately, there was a significant negative correlation between abundance and PD.A (p = 0.03) and also with soil pH (p = 0.04) (Table 2). This consistent negative correlation of pH with abundance of seedlings is reflected in a probability of 95% coefficient of pH not equal to zero out of 97% all the BMA models with coefficient of -1.619 (± 0.629) (S2 Table). In the set of models for abundance of seedlings on both sites, pH was included in less than 50% of the models, and inconsistently negatively or positively correlated with coefficient of -0.529 (± 0.677). Overall, at both sites soil pH was low (typically less than 5.0) (Table 1). Topsoil silt content had a weakest negative correlation (coefficient = -0.07, p = 0.01) with seedling presence only on the ME site (Table 2).

3.2. Shade house study: Seedlings response to light and soil treatments

After 10 months, the seedlings grown in the lowest light level had significantly lower survival rates compared with those at higher light levels (χ-squared = 83.51, df = 5, p < 0.00). While most of the seedlings at medium and high light levels survived (99% survival, only one seedling died in F.M treatment), only 19.4% of seedlings at the lowest light level survived (Table 3). The effect of soil type on seedling survival was evident at the lowest light level with 25% survival of seedlings on degraded soil compared to only 14% seedling survival on forest soil (Table 3). At the highest light level, soil type also appeared to have an effect on seedling health with a lower rate of seedlings with leaf damage (holes or marks by fungal disease or insects) on the forest soil (16.7%) compared to degraded soil (25%).

thumbnail
Table 3. Seedling survival and health status depending on soils and light levels.

https://doi.org/10.1371/journal.pone.0233524.t003

ANOVA results showed that light level, soil and light: soil interaction significantly influenced seedling height (p = 0.03; Fig 3), however, only light level resulted in a significant difference in seedling diameter (p = 0.000; Fig 3). The seedlings grown at a high light level grew higher (Low–High = -37.1, p = 0.000; Medium—High = -26.35, p = 0.000, Medium–Low = 10.75, p = 0.001) and larger (Low–High = -1.88, p = 0.000; Medium—High = -2.06, p = 0.000, Medium–Low = -0.19, p = 0.73) than those in low light levels (Fig 3). Soils significantly influenced the seedling height at the high light level treatment (p = 0.000; Fig 3A). The seedlings grown on forest soil had significantly higher stem height (Forest—Degraded = 6.39, p = 0.000; Fig 3A) and slightly larger diameters than those grown in degraded soil (Forest—Degraded = 0.15, p = 0.29; Fig 3B) and. The seedlings grown at low and medium light levels were very similar in growth with no difference between the two soils.

The data on seedling leaf characteristics after 10 months was collected from shade house component of three light levels and two soil type. Leaf morphology and anatomy were significantly different among light and soil treatments (Fig 4). Seedlings in higher light and on forest soil had greater leaves of leaf length (p < 0.001) and leaf width (p <0.001) (Fig 4A and 4B) but thinner leaf thickness (Fig 4C), except at the medium light level, leaves of seedlings on forest soil and degraded soils were not significant in length and wide. The leaves of seedlings on forested soil were thinner than those on degraded soil (p < 0.001). Leaf stomatal density was positively correlated with light levels, and seedlings on degraded soil treatments had higher leaf stomatal density compared to those on forest soil treatments (Fig 4D). Leaf chlorophyll content was negatively correlated to light level (Fig 4E). Soil type had a significant effect on chlorophyll content at both low and high light levels but not significant at the medium light level. At the low light level, seedlings on forest soil had lower leaf chlorophyll content than those on degraded soil and the opposite result was shown at high light level.

thumbnail
Fig 4. Influence of soils and light levels to leaves length (A), leaves wide (B) blade thickness (C); chlorophyll concentration (D); and stomatal density (E).

https://doi.org/10.1371/journal.pone.0233524.g004

4. Discussion

Dipterocarpus dyeri seedlings were more likely to be present at sites with lower canopy openness (Table 1, Table 2, Fig 2). Previous studies have shown that D. dyeri is a typical climax tropical shade-tolerant species in Dong Nai [42,58] and this is supported by our results. In our study, the seedlings that survived in low light level conditions had higher leaf chlorophyll content and stomata density (Fig 4) indicating that D. dyeri has high light capture efficiency at low light availability [85]. In addition, D. dyeri is a large-seeded species (S2B Fig), with recalcitrant seeds [54], a further indicator that it is a shade tolerant tropical climax species [86]. Seedlings which have high leaf area, such as D. dyeri, are more likely disadvantaged in large gaps because of dryer soil, higher temperature and greater water loss through their leaves [87]. The D. dyeri seedlings growing in the forest understory tended to have a lateral branching trait (S2C Fig), which allows maximum light capture in shade [88]. Our finding that D. dyeri seedlings occurred in sites with low light is consistent with previous research that concluded that the late-successional tropical seedlings in the Dipterocarpus genus are the most shade-tolerant genus in the Dipterocarpaceae family [42,8991].

Dipterocarpus dyeri appears to be a broadly adapted generalist dipterocarp species that can survive and grow in a broad range of light and soil conditions. The negative correlation between seedling presence and light was at odds with species abundance findings (which indicated a positive association between abundance and light) (Table 2). This result may be due to the limited range of light availability levels at our study sites (9.5% to 22%). These levels fall within the range appropriate for many shade-tolerant dipterocarps [9294]. In the shade house, survival and growth of D. dyeri was higher at the higher light levels, with only 25% of seedlings surviving at the lowest light level (5%) (Table 3). These results suggest that D. dyeri probably can persist at canopy openness lower than 10%, and that it is a generalist species rather than a shade-tolerant specialist. This is consistent with the findings of Denslow [11] and Paoli et al. [94] who found that in rainforest, most canopy species are neither open environment pioneer species nor shade-preferring “climax” forest species but generalists that can tolerate low light but require more open condition to grow into canopy trees [9597].

Dipterocarpus dyeri seedling presence had a weak negative correlation with total forest basal area (BA) (Table 2). However, at the subset of sites where the seedlings were present, their abundance was positively correlated with BA (Table 2). On the surface, this results seems counterintuitive, because typically sites with higher BA are also darker. However, in this study canopy openness was not correlated with BA (S1 Fig) because the sampling time was in the dry season, after deciduous species had dropped their leaves. Seedlings were less likely to be present at higher BA sites because these sites were characterised by a higher deciduous component, which was typically composed of Cratoxylum and Lagerstroemia species. Cratoxylum and Lagerstroemia are strongly competitive, long-lived pioneer species and, D. dyeri seedling survival is likely to be lower at these sites.

Seedling presence and abundance were strongly positively correlated with the dominance of mother trees (PD.A) (Table 2). This result was expected for a number of reasons. Firstly, the higher PD.A indicated that the site conditions were suitable for the species. Secondly, higher PD.A suggested a more stable seed source in the recovered forest [42,98,99]. Thirdly, D. dyeri is a brevideciduous species with leaf-flushing within one week (this study and [42]). It can be grouped with evergreen species similar to two other Dipterocarpus species in Thailand [72], so where it dominates basal area, the canopy in the dry season is less open (cf. deciduous forests), and lower light availability was associated with the presence of D. dyeri seedlings in our study (Fig 2). This positive correlation between presence/abundance of seedlings and mother trees contradicts previous research describing a negative effect of conspecific adult effects (due to impacts of pathogens and leaf litter) on the survival of early-stage seedlings, which was considered to be a partial explanation for the species richness in tropical forests [100103]. However, conspecific negative density effects have often been found to be a weaker factor compared to environmental conditions [47,104,105]. Conspecific density affects differently on different species, and at different stages of forest development [106]. For example, D. dyeri species produces an abundance of large seeds and large seed mass can be one of the strongest factors compensating for the conspecific negative density effect [107]. In Dong Nai, D. dyeri had been logged [58,108], resulting in the abundance of adult D. dyeri present today. Hence the density of adult D. dyeri trees might not be high enough to show the negative effects.

Dipterocarpus dyeri seedling abundance was negatively correlated with soil pH (Table 2). Overall, at all sites, soil pH was low (pH(KCl) from 3.6 to 4.0 or pH(water) of 4.5 to 5.0) (Table 1, S2 Table). Commonly, climax lowland tropical species show a high tolerance to the infertile, acidic and high aluminium concentration of tropical soils (Acrisol and Ferrasols) [20], such as occurs in dipterocarp forests. However, tropical soils can be very spatially variable and while forest soils are generally of low fertility, the higher fertility soils can be found on sloping sites where the soils are younger and have undergone less leaching [20]. The negative correlation between seedling abundance and pH is attributed to the higher tolerance of evergreen species to strongly acidic soils, compared with deciduous species, which usually prefer higher soil pH (from 5.8 to 6.2) [20]. Evergreen species are also less tolerant of low moisture than deciduous species, as occurs in these sites during the dry season. Lower pH affects the availability (or is correlated with the availability) of a range of beneficial as well as toxic minerals (aluminium, iron, manganese and phosphorus) and these are likely to be the driving factor [20]. The negative correlation between seedling abundance and soil pH was in contrast with findings for D. sublamellatus in Borneo, which was not associated with pH [94]. However, in that study the species is considered to be a soil nutrient generalist and therefore would be expected to be more tolerant of a wide range of conditions [94].

Seedling mortality was greatest in the lowest light level in the shade house trial (Table 3). The results show opposite trends in natural vs simulated (shade house) conditions; it is possible that factors other than light might have discernible influence on the presence or absence of seedlings. Local site temporal factors such as litter thickness, soil CO2 concentration, presence of herbivores and pathogens can affect germination and process of seedling establishment. In our case, there was the evidence of Fusarium wilt disease (S2D and S2E Fig), which infected the plants in the lower light and higher humidity conditions. In addition, while all seedlings were given the same amount of irrigation the soils in heavy shade appeared to stay wetter. This result was similar to the lower survival of a range of tropical species under lower light availability reported by Augspurger et al. [102] and Gaviria and Engelbrecht [109], and high mortality for Dipterocarpus seedlings at low light levels [94,110]. There are other possible and related explanations for high mortality in low light. Firstly, seedling photosynthesis was low and leading to seedlings being less able to resist disease and insect damage. Secondly, saturation of the soils could negatively affect survival of seedlings. Under the low light levels, the photosynthesis rate was low, meaning that less water was lost through leaves and evaporation from soil. Consequently, the soil, which was a Chromic Acrisol with a relatively high clay content maintained high moisture levels [65,111]. The Fe/Al-rich, acidic tropical soil may have become anoxic and therefore toxic for seedlings [112]. The heaviness of this soil may also explain the higher survival rate of seedlings on the lower clay content (degraded soil) at the same light level treatment (Table 3). Our survey also showed that adult D. dyeri were found at higher densities on the steep sites (cluster RR1 with 80% total basal area was made of D. dyeri) where the dry seasons were relatively wetter and have a shorter time for which they are waterlogged during the rainy season [17,113,114]. Thirdly, D. dyeri may be maladapted to flooding and waterlogged soils, as the species shows some morphological characteristics indicative of drought tolerance. For example, D. dyeri seedlings have hairy leaves and deep tap roots possibly giving them more tolerance to droughts [115117].

5. Conclusions

Regeneration of D. dyeri, the most dominant dipterocarp species in the region, is the key for restoring the forest landscape. D. dyeri appears to be a broadly adapted generalist dipterocarp species that can survive and grow in a broad range of light and soil conditions. D. dyeri seedlings also survived better where soils had low pH, and good drainage/dry soils rather than wet soils. The strong correlation of D. dyeri seedling presence and abundance with the dominance of mother trees is linked to the recovering status of the forest in Dong Nai. At the landscape scale, sites characterised by mixed bamboo (lower available soil water and light level [118120]) and shallow soils (on schist and shale soil parent materials) have lower presence and abundance of D. dyeri seedlings, indicating that such sites are less suitable for D. dyeri; reforestation of these sites should focus on other species. Microsite conditions, especially topographic location, impact on soil water regime in seasonally dry areas like Dong Nai, and this contributes to the observed distribution patterns of seedlings. With regard to restoration techniques, our findings suggest that (a) nurse crops are not necessary for D. dyeri establishment, if the site is moist enough, but (b) nurse crops should be used at drought-prone sites; (c) under the most common tree cover conditions, including intermediate recovered forest or dense plantation, light liberation will be necessary for native forest restoration; (d) restoration should not be attempted on waterlogged sites and (e) using phosphorus or lime carefully to increase soil phosphorus (but maintaining pH < 5.5) should be considered.

Supporting information

S2 Data. Data of site and soil characteristics at each observation point.

https://doi.org/10.1371/journal.pone.0233524.s002

(DOCX)

S1 Table. Characteristics of soil used in shade house experiment.

https://doi.org/10.1371/journal.pone.0233524.s003

(DOCX)

S2 Table. Model-averaged coefficients for site and soil effect on D. dyeri seedling presence and abundance.

Values presented are means across each Bayesian model averaging model set. For each parameter, p ≠ 0 is the probability that the coefficient is not equal to zero.

https://doi.org/10.1371/journal.pone.0233524.s004

(DOCX)

S1 Fig. Correlation of soil and site properties at both sites (A), at ME only (B), at MB only (C), and at observation points where the seedling presented only (D).

Positive correlations are displayed in grey and negative correlations in black. The size of the circle are proportional of the correlation coefficients with the significant level 0.05.

https://doi.org/10.1371/journal.pone.0233524.s005

(DOCX)

S2 Fig. Germinating seeds and seedlings when transplanted in plastic pots (A) Fruit size (B), Branching of under-canopy seedling (C), Seedling died in shade house (D) and Fusarium samples (E).

https://doi.org/10.1371/journal.pone.0233524.s006

(DOCX)

Acknowledgments

The authors thank Quang-Trung Nguyen and Anh-Linh Nguyen of DNBR for their supports of collecting data in the forest and looking after the shade house experiment.

References

  1. 1. Baldeck CA, Colgan MS, Féret J-B, Levick SR, Martin RE, Asner GP. Landscape-scale variation in plant community composition of an African savanna from airborne species mapping. Ecol Appl. 2014;24: 84–93. pmid:24640536
  2. 2. Clark DB, Palmer MW, Clark DA. Edaphic factors and the landscape-scale distributions of tropical rain forest trees. Ecology. 1999;80: 2662–2675.
  3. 3. Terborgh J. Diversity and the Tropical Rain Forest. New York: Scientific American Library; 1992.
  4. 4. Lowman MD, Rinker HB, editors. Forest Canopies. Elsevier Academic Press; 2004.
  5. 5. Lieberman D. Demography of tropical tree seedlings: a review. In: Swaine MD, editor. The ecology of tropical forest tree seedlings. Paris: UNESCO; 1996. pp. 131–135.
  6. 6. Whitmore TC. A review of some aspects of tropical rain forest seedling ecology with suggestions for further enquiry. In: Swaine MD, editor. The ecology of tropical forest tree seedlings. Paris: UNESCO; 1996. pp. 3–30.
  7. 7. Burslem DFRP. Differential responses to nutrients, shade and drought among tree seedlings of lowland tropical forest in Singapore. In: Swaine MD, editor. The Ecology of Tropical Forest Tree Seedlings. Paris: UNESCO; 1996. pp. 211–238.
  8. 8. Brienen RJW, Zuidema PA, Martínez-Ramos M. Attaining the canopy in dry and moist tropical forests: Strong differences in tree growth trajectories reflect variation in growing conditions. Oecologia. 2010;163: 485–496. pmid:20033820
  9. 9. d’Oliveira MVN, Ribas LA. Forest regeneration in artificial gaps twelve years after canopy opening in Acre State Western Amazon. For Ecol Manage. 2011;261: 1722–1731.
  10. 10. Dam O van. Forest filled with gaps: Effects of gap size on water and nutrient cycling in tropical rain forest: a study in Guyana. Tropenbos-Guyana Programme; 2001.
  11. 11. Denslow JS. Tropical rainforest gaps and tree species diversity. Annu Rev Ecol Syst. 1987;18: 431–451.
  12. 12. Nichols JD, Wagner MR, Agyeman VK, Bosu P, Cobbinah JR. Influence of artificial gaps in tropical forest on survival, growth, and Phytolyma lata attack on Milicia excelsa. For Ecol Manage. 1998;110: 353–362.
  13. 13. Clark DB, Clark DA, Rich PM. Comparative analysis of microhabitat utilization by sampling of tree species in neotropical rain forest. Biotropica. 1993;25 (4): 397–407.
  14. 14. PALMIOTTO PA, DAVIES SJ, VOGT KA, ASHTON MS, VOGT DJ, ASHTON PS. Soil-related habitat specialization in dipterocarp rain forest tree species in Borneo. J Ecol. 2004;92: 609–623.
  15. 15. Neilan W, Catterall CP, Kanowski J, McKenna S. Do frugivorous birds assist rainforest succession in weed dominated oldfield regrowth of subtropical Australia? Biol Conserv. 2006;129: 393–407.
  16. 16. Toledo M, Poorter L, Peña-Claros M, Alarcón A, Balcázar J, Leaño C, et al. Climate is a stronger driver of tree and forest growth rates than soil and disturbance. J Ecol. 2011;99: 254–264.
  17. 17. Becker P, Rabenold PE, Idol JR, Smith AP. Water potential gradients for gaps and slopes in a Panamanian tropical moist forest’s dry season. J Trop Ecol. 1988;4: 173–184.
  18. 18. Gleen-Lewin DC, van der Maarel E. Patterns and processes of vegetation dynamics. In: Glenn-Lewin DC, Peet RK, Veblen TT, editors. Plant Succession: Theory and prediction. London: Chapman & Hall; 1992. pp. 11–59.
  19. 19. Holste EK, Kobe RK, Vriesendorp CF. Seedling growth responses to soil resources in the understory of a wet tropical forest. Ecology. 2011;92: 1828–1838. Available: http://www.ncbi.nlm.nih.gov/pubmed/21939079
  20. 20. Binkley D, Fisher R. Ecology and Management of Forest Soils. 4th ed. Hoboken, NJ: Wiley-Blackwell; 2013.
  21. 21. South DB. Optimum pH for Growing Pine Seedlings. Tree Plant Notes. 2017;60: 49–62.
  22. 22. Offord CA, Meagher PF, Zimmer HC. Growing up or growing out? How soil pH and light affect seedling growth of a relictual rainforest tree. AoB Plants. 2014;6: 1–9. pmid:24790132
  23. 23. Lee DW, Oberbauer SF, Krishnapilay B, Mansor M, Mohamad H, Yap SK. Effects of irradiance and spectral quality on seedling development of two Southeast Asian Hopea species. Oecologia. 1997;110: 1–9. pmid:28307457
  24. 24. Rozendaal DMA, Hurtado VH, Poorter L. Plasticity in leaf traits of 38 tropical tree species in response to light; relationships with light demand and adult stature. Funct Ecol. 2006;20: 207–216.
  25. 25. Rozendaal DMA, Zuidema PA. Dendroecology in the tropics: A review. Trees—Struct Funct. 2011;25: 3–16.
  26. 26. Sakai A, Visaratana T, Vacharangkura T, Thai-Ngam R, Nakamura S. Growth performance of four dipterocarp species planted in a Leucaena leucocephala plantation and in an open site on degraded land under a tropical monsoon climate. Japan Agric Res Q. 2014;48: 95–104.
  27. 27. Bowman DJMS, Panton WJ. Factors that control monsoon-rainforest seedling establishment and growth in North Australian. J Ecol. 1993;81: 559–567.
  28. 28. Holl KD, Zahawi RA, Cole RJ, Ostertag R, Cordell S. Planting Seedlings in Tree Islands Versus Plantations as a Large-Scale Tropical Forest Restoration Strategy. Restor Ecol. 2011;19: 470–479.
  29. 29. Dong TL, Forrester DI, Beadle C, Doyle R, Hoang NH, Giap NX, et al. Effects of light availability on crown structure, biomass production, light absorption and light-use efficiency of Hopea odorata planted within gaps in Acacia hybrid plantations. Plant Ecol Divers. 2017;9: 1–14.
  30. 30. Cole RJ, Holl KD, Keene CL, Zahawi RA. Direct seeding of late-successional trees to restore tropical montane forest. For Ecol Manage. 2011;261: 1590–1597.
  31. 31. Dong TL, Beadle CL, Doyle R, Worledge D. Site conditions for regeneration of Hopea odorata in natural evergreen dipterocarp forest in Southern Vietnam. J Trop For Sci. 2014;26: 532–542.
  32. 32. Mayoral C, Van Breugel M, Turner BL, Asner GP, Vaughn NR, Hall JS. Effect of microsite quality and species composition on tree growth : A semi- empirical modeling approach. For Ecol Manage. 2019;432: 534–545.
  33. 33. Salinas-Peba L, Parra-Tabla V, Campo J, Munguía-Rosas MA. Survival and growth of dominant tree seedlings in seasonally tropical dry forests of Yucatan: Site and fertilization effects. J Plant Ecol. 2014;7: 470–479.
  34. 34. Maycock CR, Thewlis RN, Ghazoul J, Nilus R, Burslem DFRP. Reproduction of dipterocarps during low intensity masting events in a Bornean rain forest. J Veg Sci. 2005;16: 635–646.
  35. 35. Seidler TG, Plotkin JB. Seed dispersal and spatial pattern in tropical trees. Nathan R, editor. PLoS Biol. 2006;4: 0001–0006. pmid:17048988
  36. 36. Lutz JA, Larson AJ, Swanson ME, Freund JA. Ecological importance of large-diameter trees in a temperate mixed-conifer forest. PLoS One. 2012;7. pmid:22567132
  37. 37. Blundell AG, Peart DR. Density-dependent population dynamics of a dominant rain forest canopy tree. Ecology. 2004;85: 704–715.
  38. 38. Bagchi R, Swinfield T, Gallery RE, Lewis OT, Gripenberg S, Narayan L, et al. Testing the Janzen-Connell mechanism: Pathogens cause overcompensating density dependence in a tropical tree. Ecol Lett. 2010;13: 1262–1269. pmid:20718845
  39. 39. Inman-Narahari F, Ostertag R, Hubbell SP, Giap NX, Cordell S, Sack L. Density-dependent seedling mortality varies with light availability and species abundance in wet and dry Hawaiian forests. J Ecol. 2016;104: 773–780.
  40. 40. Wright SJ. Plant diversity in tropical forests: A review of mechanisms of species coexistence. Oecologia. 2002;130: 1–14. pmid:28547014
  41. 41. Schnitzer SA, Klironomos JN, HilleRisLambers J, Kinkel LL, Reich PB, Xiao K, et al. Soil microbes drive the classic plant diversity–productivity pattern. Ecology. 2011;92: 296–303.
  42. 42. Ghazoul J. Dipterocarp biology, ecology, and conservation. New York: Oxford University Press; 2016.
  43. 43. Appanah S, Turnbull JM, editors. A review of Dipterocarps: Taxonomy, Ecology and Silviculture. Bogor, Indonesia: Center for International Forestry Reseach; 1998.
  44. 44. Brearley FQ, Banin LF, Saner P. The ecology of the Asian dipterocarps. Plant Ecol Divers. 2016;9: 429–436.
  45. 45. Sapkota IP, Odén PC. Gap characteristics and their effects on regeneration, dominance and early growth of woody species. J Plant Ecol. 2009;2: 21–29.
  46. 46. Born J, Bagchi R, Burslem DFRP, Nilus R, Tellenbach C, Pluess AR, et al. Differential responses of dipterocarp seedlings to soil moisture and microtopography. Biotropica. 2015;47: 49–58.
  47. 47. Tito de Morais C, Ghazoul J, Maycock CR, Bagchi R, Burslem DFRP, Khoo E, et al. Understanding local patterns of genetic diversity in dipterocarps using a multi-site, multi-species approach: Implications for forest management and restoration. For Ecol Manage. 2015;356: 153–165.
  48. 48. Ashton PMS, Gunatilleke CVS. Seedling survival and growth of four Shorea species in a Sri Lankan rainforest. J Trop Ecol. 1995;11: 263–279.
  49. 49. Paine CET, Stenflo M, Philipson CD, Saner P, Bagchi R, Ong RC, et al. Differential growth responses in seedlings of ten species of Dipterocarpaceae to experimental shading and defoliation. J Trop Ecol. 2012;28: 377–384.
  50. 50. Ashton MS, Gunatilleke CV., Singhakumara BM., Gunatilleke IAUN. Restoration pathways for rain forest in southwest Sri Lanka: a review of concepts and models. For Ecol Manage. 2001;154: 409–430.
  51. 51. Bischoff W, Newbery DM, Lingenfelder M, Schnaeckel R, Petol GH, Madani L, et al. Secondary succession and dipterocarp recruitment in Bornean rain forest after logging. For Ecol Manage. 2005;218: 174–192.
  52. 52. Kettle CJ. Ecological considerations for using dipterocarps for restoration of lowland rainforest in Southeast Asia. Biodivers Conserv. 2010;19: 1137–1151.
  53. 53. Phan KL, Newman M, Khou E, Hoang VS, Vu VD, Nguyen HN, et al. Dipterocarpus dyeri. In: The IUCN Red List of Threatened Species 2017: e.T33011A2830391 [Internet]. 2017 [cited 26 Feb 2017].
  54. 54. Nguyen HN. Cây họ dầu Việt Nam (Dipterocarp species in Vietnam). Ha Noi, Vietnam: Agricultural Publishing House; 2005.
  55. 55. Langenheim JH. Plant resins: chemistry, evolution, ecology, ethnobotany. Timber Press; 2003. https://doi.org/10.1600/036364404772974374
  56. 56. Michon G, de Foresta H, Kusworo , Levang P. The Damar Agroforests of Krui, Indonesia: Justice for Forest Farmers. In: Zerner C, editor. People, Plants, and Justice: The Politics of Natural Conservation. Columbia University Press; 1999. p. 159. https://doi.org/10.4324/9781936331840
  57. 57. Budidarsono S, Arifatmi B, de Foresta H, Tomich TP. Damar Agroforest Establishment and Sources of Livelihood: A profitablility assessment of damer agroforest system in Krui, Lampung, Sumatra, Indonesia. Int Cent Res Agroforesty. Bogor, Indonesia; 2000.
  58. 58. Hai Ha NT, Duc NM, Hien DP, Duy VD, Don PQ, Tuan Anh N Le, et al. Genetic diversity of Dipterocarpus dyeri in the tropical forests of Tan Phu (Dong Nai). TAP CHI SINH HOC. 2016;38: 81–88.
  59. 59. Shugart HH. A Theory of Forest Dynamics: The Ecological Implications of Forest Succession Models. New York; Berlin: Heildelberg; Tokyo: Springer-Verlag; 1984.
  60. 60. Vanclay JK. Modelling forest growth and yield: applications to mixed tropical forests. CAB International; 1994.
  61. 61. Botkin DB. Forest Dynamics: An Ecological Model. Oxford; New York: Oxford University Press; 1993.
  62. 62. Natural Earth. Made with Natural Earth. 2020 [cited 3 Apr 2020]. https://www.naturalearthdata.com/about/terms-of-use/
  63. 63. UNESCO. Dong Nai Biosphere Reserves. 2015 [cited 12 Feb 2019]. http://www.unesco.org/new/en/natural-sciences/environment/ecological-sciences/biosphere-reserves/asia-and-the-pacific/vietnam/dong-nai/
  64. 64. Nguyễn KV, Nguyễn TH, Phan KL, Nguyễn TH. Bioclimatic Diagrams of Vietnam—Các biểu đồ sinh khí hậu Việt Nam. Ha Noi: Ha Noi National University; 2000.
  65. 65. Pham QK, Nguyen XN, Tra NP, Nguyen VK, Hua AT, Le AT. Soil map of Dong Nai Province. Ho Chi Minh City, Vietnam: MARD; 2004.
  66. 66. IUSS Working Group WRB. World reference base for soil resources 2014. International soil classification system for naming soils and creating legends for soil maps. Rome: FAO; 2014.
  67. 67. Blanc L, Maury-Lechon G, Pascal J-P. Structure, floristic composition and natural regeneration in the forests of Cat Tien National Park, Vietnam: an analysis of the successional trends. J Biogeogr. 2000;27: 141–157.
  68. 68. Thái VT. Những hệ sinh thái rừng nhiệt đới Việt Nam [Tropical forest ecosystems in Vietnam]. Ho Chi Minh City, Vietnam: Nhà xuất bản Khoa học và Kỹ Thuật [Science and Technics Publishing House]; 1999.
  69. 69. Thái VT. Phát sinh quần thể và phân loại thảm thực vật nhiệt đới ở Việt Nam [Eco-genesis and classification of forest vegetation of Vietnam (From ecosystem perspective)]. First. Hà Nội, Vietnam: Science and Techniques Publishing House; 1963.
  70. 70. McElwee PD. Forests Are Gold: Trees, People, and Environmental Rule in Vietnam. University of Washington Press; 2016.
  71. 71. Millet J, Pascal JPP, Kiet LCC. Effects of disturbance over 60 years on a lowland forest in southern vietnam. J Trop For Sci. 2010;22: 237–246. Available: http://www.tandfonline.com/doi/abs/10.1198/016214504000001303
  72. 72. Williams LJ, Bunyavejchewin S, Baker PJ. Deciduousness in a seasonal tropical forest in western Thailand : interannual and intraspecific variation in timing, duration and environmental cues. Oecologia. 2008;155: 571–582.
  73. 73. Frazer GW, Canham CD, Lertzman KP. Gap Light Analyzer (GLA): Imaging software to extract canopy structure and gap light transmission indices from true-colour fisheye photographs, users manual and program documentation. Simon Fraser University, Burnaby, British Columbia, and the Institute of Ecosystem Studies, Millbrook, New York.; 1999.
  74. 74. Nobis M. SideLook 1.1—Imaging software for the analysis of vegetation structure with true-colour photographs. 2005.
  75. 75. Nobis M, Hunziker U. Automatic thresholding for hemispherical canopy-photographs based on edge detection. Agric For Meteorol. 2005;128: 243–250.
  76. 76. Beven KJ, Kirkby MJ. A physically based, variable contributing area model of basin hydrology. Hydrol Sci Bull. 1979;24: 43–69.
  77. 77. Raduła MW, Szymura TH, Szymura M. Topographic wetness index explains soil moisture better than bioindication with Ellenberg’s indicator values. Ecol Indic. 2018;85: 172–179.
  78. 78. Sørensen R, Zinko U, Seibert J. On the calculation of the topographic wetness index: Evaluation of different methods based on field observations. Hydrol Earth Syst Sci. 2006;10: 101–112.
  79. 79. R Development Core Team. R: A language and environment for statistical computing. Vienna, Austria: R Foundation for Statistical Computing; 2018. https://www.r-project.org/
  80. 80. Wang Y, Naumann U, Wright ST, Warton DI. Mvabund- an R package for model-based analysis of multivariate abundance data. Methods Ecol Evol. 2012;3: 471–474.
  81. 81. Wang Y, Naumann U, Eddelbuettel D, Warton D, Byrnes J, Silva R dos S, et al. mvabund: Statistical Methods for Analysing Multivariate Abundance Data. 2018. https://cran.r-project.org/package=mvabund.
  82. 82. Venables WN, Ripley BD. Modern Applied Statistics with S. Fourth. New York: Springer; 2002.
  83. 83. Bates D, Mächler M, Bolker B, Walker S. Fitting Linear Mixed-Effects Models using lme4. J Stat Softw. 2015;67: 1–48.
  84. 84. Bååth R. Bayesian First Aid. tba; 2013. tba
  85. 85. Kenzo T, Yoneda R, Matsumoto Y, Azani MA, Majid NM. Leaf photosynthetic and growth responses on four tropical tree species to different light conditions in degraded tropical secondary forest, Peninsular Malaysia. Jarq-Japan Agric Res Q. 2008;42: 299–306.
  86. 86. Baskin CC, Baskin JM. Seed dormancy in trees of climax tropical vegetation types. Trop Ecol. 2005;46: 17–28.
  87. 87. O’Brien MJ, Philipson CD, Tay J, Hector A. The Influence of variable rainfall frequency on germination and early growth of shade-tolerant dipterocarp seedlings in Borneo. PLoS One. 2013;8: 1–9. pmid:23894634
  88. 88. Zipperlen SW, Press MC. Photosynthesis in relation to growth and seedling ecology of two dipterocarp rain forest tree species. J Ecol. 1996;84: 863–876.
  89. 89. Cao K, Booth EW. Leaf anatomical structure and photosynthetic induction for seedlings of five dipterocarp species under contrasting light conditions in a Bornean heath forest. J Trop Ecol. 2001;17: 163–175.
  90. 90. Chua SC, Potts MD. The role of plant functional traits in understanding forest recovery in wet tropical secondary forests. Sci Total Environ. 2018;642: 1252–1262. pmid:30045506
  91. 91. Ashton MS, Gunatilleke CVS, Gunatilleke IAUN, Singhakumara BMP, Gamage S, Shibayama T, et al. Restoration of rain forest beneath pine plantations: A relay floristic model with special application to tropical South Asia. For Ecol Manage. 2014;329: 351–359.
  92. 92. Griscom HP, Ashton MS. Restoration of dry tropical forests in Central America: A review of pattern and process. For Ecol Manage. 2011;261: 1564–1579.
  93. 93. Ashton PMS, Goodale UM, Bawa KS, Ashton PS, David Neidel J. Restoring working forests in human dominated landscapes of tropical South Asia: An introduction. For Ecol Manage. 2014;329: 335–339.
  94. 94. Paoli GDD, Curran LMM, Zak DRR. Soil nutrients and beta diversity in the Bornean Dipterocarpaceae: evidence for niche partitioning by tropical rain forest trees. J Ecol. 2006;94: 157–170.
  95. 95. Whitmore TC, Brown ND. Dipterocarp seedling growth in rain forest canopy gaps during six and a half years. Philos Trans R Soc London Ser B Biol Sci. 1996;351: 1195–1203.
  96. 96. Itoh A, Yamakura T, Ogino K, Lee HS. Survivorship and growth of seedlings of four dipterocarp species in a tropical rainforest of Sarawak, East Malaysia. Ecol Res. 1995;10: 327–338.
  97. 97. Islam M, Salim SH, Kawsar MH, Rahman M. The effect of soil moisture content and forest canopy openness on the regeneration of Dipterocarpus turbinatus C.F. Gaertn. (Dipterocarpaceae) in a protected forest area of Bangladesh. Trop Ecol. 2016;57: 455–464.
  98. 98. Weiskittel AR, Hann DW, Kershaw JA, Vanclay JK. Forest Growth and Yield Modeling. Chichester, UK: John Wiley & Sons, Ltd; 2011. https://doi.org/10.1002/9781119998518
  99. 99. Chong KY, Chong R, Tan LWA, Yee ATK, Chua MAH, Wong KM, et al. Seed production and survival of four dipterocarp species in degraded forests in Singapore. Plant Ecol Divers. 2016;9: 483–490.
  100. 100. Bagchi R, Henrys PA, Brown PE, Burslem DFRP, Diggle PJ, Gunatilleke CVS, et al. Spatial patterns reveal negative density dependence and habitat associations in tropical trees. Ecology. 2011;92: 1723–1729. pmid:21939068
  101. 101. Bagchi R, Press MC, Scholes JD. Evolutionary history and distance dependence control survival of dipterocarp seedlings. Ecol Lett. 2010;13: 51–59. pmid:19849708
  102. 102. Augspurger CK, Kelly CK, Kelly CK, Augspurger CK. Pathogen mortality of tropical tree seedlings: studies of the effects of dispersal distance, experimental seedling density, and light conditions. Oecologia. 1984;61: 211–217.
  103. 103. Liu H, Shen G, Ma Z, Yang Q, Xia J, Fang X, et al. Conspecific leaf litter-mediated effect of conspecific adult neighborhood on early-stage seedling survival in a subtropical forest. Sci Rep. 2016;6: 1–8. pmid:27886275
  104. 104. Mangan SA, Schnitzer SA, Herre EA, MacK KML, Valencia MC, Sanchez EI, et al. Negative plant-soil feedback predicts tree-species relative abundance in a tropical forest. Nature. 2010;466: 752–755. pmid:20581819
  105. 105. Schnitzer SA, Carson WP. Treefall gaps and the maintenance of species diversity in a tropical forest. Ecology. 2001;82: 913–919.
  106. 106. Oshima C, Tokumoto Y, Nakagawa M. Biotic and abiotic drivers of dipterocarp seedling survival following mast fruiting in Malaysian Borneo. J Trop Ecol. 2015;31: 129–137.
  107. 107. Lebrija-Trejos E, Reich PB, Hernández A, Wright SJ. Species with greater seed mass are more tolerant of conspecific neighbours: a key driver of early survival and future abundances in a tropical forest. Ecol Lett. 2016;19: 1071–1080. pmid:27346439
  108. 108. Nguyễn XQ. Nghiên cứu ảnh hưởng của chất độc da cam/Dioxin lên quá trình diễn thế các hệ sinh thái và sự biến đổi cấu trúc gen, protein của một số loài sinh vật tại khu vực Mã Đà. Minist Sicence Technol. Hà Nội, Viet Nam: Bộ Khoa học và Công Nghệ (Ministry of Science and Technology); 2010.
  109. 109. Gaviria J, Engelbrecht BMJ. Effects of drought, pest pressure and light availability on seedling establishment and growth: Their role for distribution of tree species across a tropical rainfall gradient. PLoS One. 2015;10: e0143955. pmid:26619138
  110. 110. Ashton PMS, Gamage S, Gunatilleke IAUN, Gunatilleke CVS. Restoration of a Sri Lankan Rainforest: Using Caribbean Pine Pinus caribaea as a Nurse for Establishing Late-Successional Tree Species. J Appl Ecol. 1997;34: 915.
  111. 111. Fookes PG, editor. Tropical Residual Soils. London: The Geological Society; 1997.
  112. 112. Silver WL, Lugo AE, Keller M. Soil oxygen availability and biogeochemistry along rainfall and topographic gradients in upland wet tropical forest soils. Biogeochemistry. 1999;44: 301–328.
  113. 113. Ito S, Mizoue N, Kajisa T, Heng Sokh VM, Hirata R, Mitsuda Y. Analysis of growth traits of Hopea recopei and Dipterocarpus obtusifolius growing in a young secondary forest in Kampong Chhnang, Cambodia. In: International Forestry Review, editor. Forests for the Future: Sustaining Society and the Environment XXIII IUFRO World Congress. Seoul: COMMONWEALTH FORESTRY ASSOCIATION; 2010.
  114. 114. Deb JC, Phinn S, Butt N, McAlpine CA. The impact of climate change on the distribution of two threatened Dipterocarp trees. Ecol Evol. 2017;7: 2238–2248. pmid:28405287
  115. 115. Cao K. Water relations and gas exchange of tropical saplings during a prolonged drought in a Bornean heath forest, with reference to root architecture. J Trop Ecol. 2000;16: S0266467400001292.
  116. 116. Hattori D, Kenzo T, Yamauchi N, Irino KO, Kendawang JJ, Ninomiya I, et al. Effects of environmental factors on growth and mortality of Parashorea macrophylla (Dipterocarpaceae) planted on slopes and valleys in a degraded tropical secondary forest in Sarawak, Malaysia. Soil Sci Plant Nutr. 2013;59: 218–228.
  117. 117. Comita LS, Engelbrecht BMJ. Drought as a driver of tropical tree species regeneration dynamics and distribution patterns. In: Commes DA, Burslem DFRP, Simonson WD, editors. Forests and Global Change. Cambridge University Press; 2014. pp. 261–308. https://doi.org/10.1017/cbo9781107323506.013
  118. 118. Takahashi K, Uemura S, Suzuki JI, Hara T. Effects of understory dwarf bamboo on soil water and the growth of overstory trees in a dense secondary Betula ermanii forest, northern Japan. Ecol Res. 2003;18: 767–774.
  119. 119. Rother DC, Rodrigues RR, Pizo MA. Effects of bamboo stands on seed rain and seed limitation in a rainforest. For Ecol Manage. 2009;257: 885–892.
  120. 120. Larpkern P, Moe SR, Totland Ø. Bamboo dominance reduces tree regeneration in a disturbed tropical forest. Oecologia. 2011;165: 161–168. pmid:20607296