Journal of Ecology and Environment

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Published online August 18, 2022

Journal of Ecology and Environment (2022) 46:21

© The Ecological Society of Korea.

Effects of reforestation approaches, agroforestry and woodlot, on plant community composition, diversity and soil properties in Madhupur Sal forest, Bangladesh

Mohammad Kamrul Hasan* , Md. Tariqul Islam , Rojina Akter and Nasima Akther Roshni

Department of Agroforestry, Faculty of Agriculture, Bangladesh Agricultural University, Mymensingh 2202, Bangladesh

Correspondence to:Mohammad Kamrul Hasan

Received: May 20, 2022; Revised: July 18, 2022; Accepted: July 22, 2022

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Background: Increasing land demands for food production have led to biodiversity loss and land degradation in the Madhupur Sal forest. Reforestation activities such as agroforestry and woodlot plantation support the conservation of diversity, restoration of forest and prevention of soil erosion in degraded natural Sal forest. Knowing about these reforestation activities, this study is needed to compare the species composition, richness, and soil nutrients of these two plantation activities to the natural Sal forest in the degraded Madhupur Sal forest in Bangladesh.
Results: The analysis showed that in between the reforestation activities, the highest Shannon- Wiener index (1.79), evenness (0.60) and Simpson’s index (0.79) were found in the agroforestry site compared to the woodlot plantation site. On the contrary, the highest species richness (n = 14), tree basal area (19.56 m2 ha−1, Margalef’s index (1.96) were recorded in woodlot plantation than in the agroforestry site. We observed that at 0–15 cm depth, soil organic matter (2.39%), total nitrogen (0.14%), available phosphorous (62.67 μg g−1) and exchangeable potassium (0.36 meq/100 g) in agroforestry plots were significantly higher compared to other forest sites. At topsoil (15–30 cm depth), soil organic matter (1.67%) and available phosphorous (21.09 μg g−1) were found to be higher in agroforestry site.
Conclusions: Both reforestation approaches improved soil function, although woodlot plantation had the higher species richness. Therefore, plantation activities by the sustainable implementation of these two practices are the best alternative to restore the biodiversity, richness and conserve soil fertility in the Madhupur Sal forest of Bangladesh.

Keywords: deciduous forest, dendrogram, reforestation program, Shannon-Wiener index, soil nutrient status, species richness

The moist deciduous Sal (Shorea robusta) forests are Bangladesh’s greatest biodiverse and ecologically significant natural forests. The inland Sal forest area is 120,000 ha, out of which the central region accounts for 86%, whereas the northern part only accounts for 14% (Bangladesh Forest Department 2017; Hasan et al. 2020). The large belt of Sal forest lies in the districts of greater Dhaka, Mymensingh and Tangail, known as the “Madhupur Tract” consisting of Madhupur and Bhawal Garh (Rahman and Vacik 2010) that exhibits the distinct characteristics of Bangladesh’s Sal forest. It showed about 36% of the original Sal forest cover was existed in 1985 (Masum et al. 2016) and the remaining was in jeopardy (Alam et al. 2008). The area of Madhupur Sal forest was 24,150 ha (Khan and Naher 2020), but the forest has shrunk to 18,235 ha. Previous studies of floral compositions indicated that Madhupur Sal forest had the richest plant diversity (tree, shrub, climbers and herb) (Alam 1995; Malaker et al. 2010; Rahman et al. 2009). Until the early 20th century, Madhupur Sal forest was a biodiversity hotspot, but rapid human pressure has caused them the most vulnerable habitat for flora and wildlife. People living in forest are depleting its natural resources and encroaching on it or taking it over, causing a rapid change in the forest’s land-use pattern (Gain 2002; Rahman et al. 2009; Rahman et al. 2010). Notably, local communities heavily rely on these forest ecosystems for their livelihood, resulting to worrisome biodiversity losses. Thus, large expanses of forestland are being converted to agricultural fields for high-demand farm crops in Madhupur Sal Forest (Islam et al. 2019).

Viewing the purposes of conservation and safeguard of natural Sal forest, the Bangladesh Forest Department has implemented numerous forest management and conservation approaches. As part of conservation strategies, the Government declared Madhupur Sal Forest as National Park (area 8,436 ha) in 1962 to conserve forest genetic resources. In 1989, the Forest Department introduced participatory forestry programs -woodlot and agroforestry under Thana Afforestation and Nursery Development project in Sal forests (Alam et al. 2008; Rana et al. 2007; Salam and Noguchi 2005). Considering success rate, agroforestry and woodlot plantations were suggested for the degraded Sal forests as part of the Forestry Sector Project, which was launched between 1997 to 2004 (Alam et al. 2008). To protect biodiversity, the Forest Department had also implemented Sal coppice management, protected area management, and buffer zone management strategies. However, some of these initiatives fell short, and forest encroachment persisted (Local Forest Office 2013). But woodlot and agroforestry activities were still practiced as reforestation approaches on encroached forestlands. Many authors regard agroforestry and woodlot management crucial for sustainable Sal forest development and maintenance (Bangladesh Forest Department 2017; Islam et al. 2013; Rana et al. 2007; Salam and Noguchi 2005).

Participatory forestry programs are considered an economically viable program to manage disrupted Madhupur Sal forest in Bangladesh. Local farmers are cultivating agronomic crops alongside multipurpose trees (fruit, timber, fuel and medicinal species) on government-owned degraded land under these practices. These programs have proved successful (Muhammed et al. 2008) and become very productive for forest biodiversity conservation in the Madhupur Sal forest region (Islam et al. 2022). The participatory programs have restored forest diversity and soil degradation by reinstating soil fertility and planting practices (Islam et al. 2012; Roy et al. 2014). While conventional forest management led to a gross loss of forest cover, participatory forestry extends the vegetation cover and reconciles ecological factors. Paudel et al. (2021) mentioned that participatory forestry approaches met the objectives of forest conservation on sustainable basis in Nepal. Zheng et al. (2008) found that reforestation activities significantly affected plant structure and soil erosion in Southern China’s hilly forest area. In a nutshell, reforestation approaches are vital for protecting biodiversity, ecological balance, soil conservation in degraded tropical moist deciduous forests in Bangladesh and globally.

The existing literature of Madhupur Sal forest has focused on the role of participatory forestry program for community development (Islam 2019; Islam and Sato 2012). Previously, several studies were carried out on the species composition, biodiversity and soil nutrients of agroforestry practices compared to natural forests in many parts of Bangladesh and India (Chowdhury et al. 2022; Kibria and Saha 2011; Nandy and Das 2013). To the best of our knowledge, no large scale investigation of the impacts of reforestation activities on plant community, diversity and soil quality in deforested area in Bangladesh has been conducted. There is still a research void to what extent the reforestation activities have impacted plant composition, diversity and soil nutrients in the degraded Sal forest. Thus, the study had two goals: first, to explore tree stand community, diversity and soil properties of reforestation activities like agroforestry and woodlot plantations in the degraded natural Sal forest in Madhupur; second, to compare the effects of these reforestation activities with natural forest in terms of the stand community, diversity and soil properties in the Madhupur Sal forest.

This study helps policymakers understand which reforestation activities work best to restore biodiversity and conserve soil in tropical moist deciduous forests. This study also provides scientific information on the significant effects of reforestation approaches and management practices; soil fertility improvement, ecosystem services, development of plant community and carbon sequestration in the degraded forest in Bangladesh. Thus, it helps to build forest policies to reduce deforestation and land degradation in the depleted Sal forestland of Bangladesh.

Study area

The study was done in the Madhupur Sal forest, which officially comprises portions of the Tangail and Mymensingh districts of Bangladesh. The Madhupur Sal forest is located between 23° 50 and 24° 50’ N and 89° 54 to 90° 50’ E (Fig. 1). The participatory agroforestry program was implanted in the four ranges (sub-divisions) of Tangail district and the Rasulpur range of Mymensingh forest division. The study selected three ranges: Dhokola, Auronkolaa, and Rasulpur ranges, because these areas are mostly encroached and hold reforestation activities to manage deforestation.

Figure 1. Forest map of Bangladesh showing the selected study areas of Madhupur Sal forest under (A) Tangail and (B) Mymensingh forest division.

Description of the woodlot and agroforestry program

The woodlot and agroforestry plantation schemes were successfully implemented in the Madhupur Sal forest. Participants can continue for up to 30 years with both programs if they meet program criteria. The Future Tree Farming Fund received 10% of the tree outputs, while the Forest Department received 45%. Participants do not have to share the crop benefit if they plant crops with trees during the program cycle. Each participant in both programs got 1 ha of degraded forest land for a 10-year woodlot planting cycle. The Forest Department (FD) selected the fast-growing tree species (akashmoni, hybrid, eucalyptus, gamar, mahagony etc.) under the woodlot plantation (2,500 trees ha−1) by 2 m × 2 m model where tree species were planted with a row to row and plant to plant spacing of 2 m × 2 m. In case of agroforestry, the FD suggested the tree species of akashmoni, bokain, mangium, goraneem, horitoki, bohera, agar etc. for plantation in the plots. In 2 m × 2 m model, first 4 m2 areas of land were utilized for tree plantations (750 trees ha−1) while the next 20 m areas were kept for agricultural crops such as herbaceous plants (pineapple, banana, papaya, ginger, turmeric, aroid etc.). Following the crop zone, a tree zone of 4 m2 was set aside, and this process was repeated until the agroforestry plot was entirely filled. After four years of establishment of woodlot plantation, half of the remaining trees were thinned, and the process was repeated after seven years. But in agroforestry, only 50% of the thinning was done in the seventh year of the cycle. After a 10-year cycle, the remaining trees have been harvested and the benefits shared in the woodlot projects.

Design of sampling and plot measurement

The study sites are divided based on participatory forestry and/or reforestation activities into three sites, viz; agroforestry site (AF), woodlot plantation (WL) and natural Sal forest site (NSF), which are considered as the treatment of the study. This study dealt with sampling frames. A total of 180 quadrate plots from the selected ranges were measured following random sampling. Of which 120 plots are participants’ plots (4 to 10 years old aged tree species of agroforestry and woodlot plantation site) and 60 plots (different aged tree species) in the natural Sal forest site. The area of each quadrate plot was 100 m2 and was used for the investigation of mature trees (≥ 5 cm diameter at breast height [DBH]). Within each quadrate plot, tree species parameters like the name of tree species, the number of tree species, tree basal girth were recorded through forest inventory. The girth at breast height of all the trees was measured at 1.37 m. A Suunto Clinometer was used to measure the total height of all trees. At the same time, a total of 180 soil samples were separately collected from each of both 0–15 cm and 15–30 cm soil depths from the study sites to analyze soil nutrient status.

Data analysis

Ecological parameters of tree species at three sites

The field data was assessed for number of species and quantitative analysis of frequency; density per ha (Shukla and Chandel 2000) and basal area per ha (Chowdhury et al. 2019; Shukla and Chandel 2000) and their relative values were calculated and summed to get importance value index (IVI). Relative density and frequency (Dallmeier et al. 1992; Misra 1968); relative dominance (Chowdhury et al. 2019) were calculated for quantitative analysis of tree species in the study area. The following diversity indices were also calculated: species richness, Shannon–Wiener diversity index (Shannon and Wiener 1963), Simpson’s index (Simpson 1949), Margalef’s index (Margalef 1958); Evenness (Magurran 1988) and Similarity index (Jaccard 1912). The abundance-to-frequency ratio explained the species’ distribution pattern (Whitford 1949) and total tree species in different sample sizes were used to create species–area curves (Rahman et al. 2009).

Chemical analysis of soil samples

Soil samples were prepared and analyzed at the Soil Resources Development Institute. The pH of the soil was tested using a glass electrode pH meter. The wet oxidation technique was used to determine organic carbon (Walkley and Black 1934). The organic matter was then determined by multiplying the organic carbon content by the Van Bemmelen factor of 1.73. The micro-Kjeldahl technique was used to quantify total nitrogen (Jackson 1958). The available phosphorus in soil samples were determined by extracting the soil with 0.5 M NaHCO3 solution having pH 8.5 following Bray and Kurtz method as described by Jackson (1958). The 1N NH4OAc extract technique was used to determine exchangeable K using a flame photometer (Page et al. 1982).

Statistical analysis of data

All data from different sources were tabulated and evaluated separately. All the graphs were created using Microsoft Excel (Microsoft corporation, Washington DC, USA) and Minitab 19 (LLC, State College, PA, USA). PAST (version 4.08) was used to create a hierarchical cluster dendrogram and calculate biodiversity indices. R statistical program (3.6.3) was used for descriptive analysis (minimum, maximum, median, quartiles values) of all soil samples (n = 180 for each soil depth) and presented as boxplots. Significance differences of mean were adjusted statistically according to Tukey’s HSD test (One-way ANOVA) at p = 0.05 using same statistical program.

Identification of tree species in the study area

We recorded a total of 49 tree species from three sites in the study area in Madhupur Sal forest (Table 1). From the result, it represented different tree species identified in the study area and also described the tree species name with their scientific name, family name and inhabit (Table 1).

Table 1 . List of identified tree species of the study area in the Madhupur Sal forest.

Serial no.Local nameScientific nameFamily Inhabit
1AgarAquilaria agallochaThymelaeaceaeWL, AF
2AkashmoniAcacia auriculiformisMimosaceaeWL, AF
3AmlokiPhyllanthus emblicaEuphorbiaceaeNSF
4AmraSpondias mombinAnacardiaceaeWL
5ArjunTerminalia arjunaCombretaceaeNSF
6AshwathaFicus religiosaMoraceaeNSF
7AzuliDillenia pentagynaDilleniaceaeNSF
8BhutumHymenodictyon excelsumRubiaceaeNSF
9BoheraTerminalia belliricaCombretaceaeNSF
10Bolla gota, BohalCordia dichotomaBoraginaceaeNSF
11BonamraSpondias pinnataAnacardiaceaeNSF
12BotFicus benghalensisMoraceaeNSF
13ChaltaDillenia indicaDilleniaceaeWL
14ChapalishArtocarpus chaplasaMoraceaeAF, NSF
15ChokakolaBauhinia malabaricaCaesalpiniaceaeNSF
16DebdaruPolyalthia longifoliaAnnonaceaeNSF
17Gadila, KumviCareya arboreaLecythidaceaeNSF
18GamarGmelina arboreaLamiaceaeWL
19GarjanDipterocarpus turbinatusDipterocarpaceaeNSF
20GuavaPsidium guajavaMyrtaceaeAF
21GoraneemMelia azedarachMeliaceaeWL
22HybridAcacia hybridFabaceaeWL, AF
23JackfruitArtocarpus heterophyllusMoraceaeWL, AF
24Jagya dumurFicus racemosaMoraceaeNSF
25JarulLagerstroemia speciosaLythraceaeWL, NSF
26JigaLamnea coromandelicaBurseraceaeNSF
27JamSyzygium cuminiMyrtaceaeNSF
28JoinaSchleichera oleosaSapindaceaeNSF
29KadamAnthocephalus chinensisRubiaceaceWL
30Kaika, halduHaldina cordifoliaRubiaceaceNSF
31KanchonBauhinia variegataFabaceaeNSF
32KharajoraLitsea glutinosaLauraceaeNSF
33Khulla damorGrewia serrulataTiliaceaeNSF
34LitchiLitchi chinensisSapindaceaeAF
35LohakathXylia xylocarpaMimosaceaeNSF
36MahoganySwietenia mahoganyMeliaceaeAF, WL
37ManderErythrina variegataFabaceaeNSF
38MangoMangifera indicaAnacardiaceaeAF, WL
39NeemAzadirachta indicaMeliaceaeWL
40NeulBursera serrateBurseraceaeNSF
41OjhaCryptocarya amygdalinaLauraceaeNSF
42PitrajAphanamixis polystachyaMimosaceaeNSF
43SalShorea robustaDipterocarpaceaeNSF
44SheoraStreblus asperMoraceaeNSF
45ShidaiLagerstroemia parvifloraLythraceaeNSF
46SinduriMallotus philippensisEuphorbiaceaeNSF
47SilkoroiAlbizia proceraMimosaceaeNSF
48SonaluCassia fistulaCaesalpiniaceaeNSF
49Teak/ SegunTectona grandisLamiaceaeAF, WL

AF: agroforestry site; WL: woodlot plantation site; NSF: natural Sal forest site.

Community structure of tree species based on Basal area (m2 ha−1), DBH (cm) and Height (m) class

Basal area (m2 ha−1)

The highest basal area (24.57 m2 ha−1) was found in natural forest site than other two plantation sites (Fig. 2). In between the participatory activities, we recorded the highest basal area (19.56 m2 ha−1) in woodlot plantation and the lowest basal area (12.1 m2 ha−1) in agroforestry site (Fig. 2).

Figure 2. Bar diagram showing the basal area (m2 ha−1) of tree species at three forest sites in the study area. AF: agroforestry site; WL: woodlot plantation site; NSF: natural Sal forest site.

Diameter at breast height (cm) class

The highest number of tree species in agroforestry and woodlot plantation site ranged from DBH of 11–15 cm which was followed by the DBH range of 6–10 cm (Fig. 3A). It was noted the highest number of tree species in natural Sal forest ranged from DBH of 21–25 cm and that the larger trees (DBH > 25 cm) were found only in the natural Sal forest site (Fig. 3A).

Figure 3. Distribution of number of trees based on (A) DBH class (cm) and (B) Height class (m) of three forest sites in the study area. DBH: diameter at breast height; AF: agroforestry site; WL: woodlot plantation site; NSF: natural Sal forest site.

Height (m) class

The tree height distributions were typical in all the three forest sites. Agroforestry site had shorter tree species (< 15 m), while woodlot plantation and natural Sal forest site had taller trees (Fig. 3B). Naturalness increases the proportion of taller trees, but protection level seems not to have an influence on tree height.

Species composition analysis of trees at three forest sites in the study area

Cluster analysis

A hierarchical cluster dendrogram was constructed which depicted the distribution of identified number of tree individuals across all study’s sample plots (Fig. 4). The data matrix contained 180 plots and 49 tree species. Three sites were differentiated from each other based on their number of individuals (Fig. 4).

Figure 4. Dendrogram showing the number of tree species of sample plots in three forest sites of the study area.

Species area curve

Species-area curves showed that the number of sample plots captured the available tree species in the study area. The maximum number of tree species was captured at all the plots of natural Sal forest site because of highest species richness (n = 34) (Fig. 5). In natural Sal forest site, the number of tree species continued to increase in up to 50 plots, in woodlot plantation site only a small number of additional plant species were identified after 30 plots (Fig. 5).

Figure 5. Species-area curves showing the number of tree species for study plots in the study area. AF: agroforestry site; WL: woodlot plantation site; NSF: natural Sal forest site.

Relative frequency, relative density, relative dominance and important value index

From the result, it has been found that in the agroforestry site, the highest relative density was represented by Acacia auriculiformis (32.67%) followed by Aquilaria malaccensis (21.51%), Mangifera indica (19.92%), Acacia hybrid (7.57%), Psidium guajava (6.37%) and also in the woodlot plantation site, the highest relative density were represented by Acacia auriculiformis (51.54%) followed by Anthocephalus chinensis (9.09%), Acacia hybrid (6.27%), Aquilaria malaccensis (3.47%), Lagerstroemia speciosa (5.21%) (Table 2). In the natural Sal forest site, the highest relative density was represented by Shorea robusta (65.89 %) followed by Dipterocarpus turbinatus (3.10%), Bursera serrata (3.10%), Bauhinia variegata (2.58%), Dillenia pentagyna (2.45%) (Table 2).

Table 2 . Relative density, relative frequency, relative dominance and important value index (IVI) of the enlisted tree species of all three sites.

Scientific name of
tree species
density (%Rd)
frequency (%Rf)
dominance (%Rdo)
Acacia auriculiformis32.6751.54-32.9134.65-31.2939.96-96.86126.15-
Acacia hybrid7.576.27-12.6612.87-10.4710.69-30.6929.84-
Albizia procera--0.13--0.43--0.05--0.61
Anthocephalus chinensis-9.09--9.90--9.09--28.07-
Aphanamixis polystachya--1.03--1.72--0.22--2.97
Aquilaria malaccensis21.513.4715.191.9819.413.1156.118.56-
Artocarpus chaplasa1.943.431.576.94
Artocarpus heterophyllus1.391.741.165.065.942.142.432.280.678.889.963.99
Azadirachta indica-3.60--6.93--5.63--16.16-
Bauhinia malabarica--0.39--1.28--0.69--2.37
Bauhinia variegata--2.58--6.00--0.84--9.44
Bursera serrata--3.10--4.72--2.19--10.01
Cordia dichotoma--0.39--1.28--0.56--2.24
Cryptocarya amygdalina--1.29--2.15--0.43--3.87
Dillenia indica-0.40--0.99--0.18--1.57-
Dillenia pentagyna--2.45--4.72--2.48--9.66
Dipterocarpus turbinatus--3.10--3.43--1.34--7.87
Erythrina variegata--0.64--1.72--0.27--2.63
Ficus benghalensis--0.26--0.86--10.34--11.45
Ficus racemosa--0.52--1.72--1.29--3.53
Ficus religiosa--0.13--0.43--3.45--4.01
Careya arborea--0.52--1.28--0.21--2.01
Gmelina arborea-2.94--5.94--4.16--13.04-
Grewia serrulata--0.77--1.72--0.44--2.94
Haldina cordifolia--0.13--0.43--0.07--0.62
Hymenodictyon excelsum--0.52--1.72--1.68--3.92
Lagerstroemia parviflora--1.29--2.57--1.47--5.34
Lagerstroemia speciosa-5.211.30-3.963.00-9.510.37-18.674.66
Lamnea coromandelica--1.03--3.43--0.99--5.45
Litchi chinensis3.78--3.79--7.36--14.94-
Litsea glutinosa-0.13--0.43--0.09--0.65
Mangifera indica19.92--16.45--19.39--55.77-
Mallotus philippensis--2.97--6.87--1.08--10.92
Melia azedarach-2.44--1.92--3.73--8.09
Phyllanthus emblica--0.38--0.86--0.06--1.30
Polyalthia longifolia--0.39--0.87--0.58--1.83
Psidium guajava6.37--6.33--7.36--20.06--
Schleichera oleosa--0.64--1.72--0.49--2.86
Shorea robusta--65.89--25.75--59.01--150.65
Spondias momdin-0.27-0.99--0.63--1.88-
Spondias pinnata--1.42--3.86--0.87--6.15
Streblus asper--0.52--1.29--0.11--1.91
Syzygium cumini2.08--0.96--2.01--5.05-
Swietenia mahogany-14.15--11.88--12.86--38.90-
Terminalia arjuna--0.13--0.43--0.42--0.98
Terminalia bellirica--2.19--6.01--5.09--13.30
Xylia xylocarpa--0.39--0.86--0.46--1.70
Cassia fistula--0.26--0.86--0.06--1.18
Tectona grandis0.401.34-1.263.96-0.851.88-2.517.18-

AF: agroforestry site; WL: woodlot plantation site; NSF: natural Sal forest site; -: indicates absent.

In the agroforestry site species with the highest relative frequency was found in Acacia auriculiformis (32.91%) followed by Mangifera indica (16.45%), Aquilaria malaccensis (15.19%) and the lowest relative frequency was found in the species of Litchi chinensis (3.79%). Whereas in the woodlot plantation site, relative frequency was found maximum in Acacia auriculiformis (34.65%) followed by Acacia hybrid (12.87%) and Swietenia mahogany (11.88%) (Table 2). In the natural Sal forest site species, Shorea robusta was dominant species with relative frequency (25.75%) followed by Mallotus philippensis (6.87%) and Bauhinia variegata (6.0%) (Table 2).

In agroforestry site, the result depicted that species with the highest relative dominance was found in Acacia auriculiformis (31.29%) followed by Aquilaria malaccensis (19.41%) and then by Mangifera indica (19.39%) and the lowest relative dominance was found in the species of Artocarpus heterophyllus (2.43%). Whereas in the woodlot plantation site species with the highest relative dominance was found in Acacia auriculiformis (39.96%) and the lowest relative dominance was found in the species of Dillenia indica (0.18%) followed by Spondias momdin (0.63%). In the other, from the natural Sal forest site, it was observed that the highest relative dominance 59.01% which was found from Shorea robusta followed by Ficus benghalensis (10.34%). In the other hand the lowest relative dominance was found in Albizia procera and which was (0.05%) (Table 2).

After calculation of relative frequency, relative density and relative dominance in the agroforestry site, the highest IVI (96.86%) was found in the species of Acacia auriculiformis and the second-highest IVI in Aquilaria malaccensis (56.11%) followed by Mangifera indica (55.77%). Whereas in the woodlot plantation site, IVI was maximum in Acacia auriculiformis (126.15%) followed by Swietenia mahogany (38.90%), Acacia spp. (29.84%) and the lowest was found in Dillenia indica (1.57%) (Table 2). In the natural Sal forest site, the highest IVI (150.65%) was found in the species of Shorea robusta followed by Terminalia bellirica (13.30%), Mallotus philippensis (10.92%) and Bursera serrata (10.01%). The lowest IVI was found in Albiia procera (0.61%) (Table 2).

Diversity analysis of tree species community at three forest sites

Taxonomic composition of tree species

In agroforestry site, we found 10 tree species belonging to 9 genera and 8 families. Similarly, in woodlot plantation site, we recorded 14 tree species (13 genera and 11 families) and 34 tree species (29 genera and 21 families) from natural Sal forest site in the study area (Table 3).

Table 3 . Species richness, overlapping, similarity index and distribution pattern (%) of tree species in three forest sites of the study area.

Taxonomic parametersAFWLNSFAF–WLAF–NSFWL–NSF
Number of species/ richness101434---
Number of families81121---
Number of genera91329---
Species overlapping---711
Similarity index---0.410.020.02
Distribution pattern (%)

AF: agroforestry site; WL: woodlot plantation site; NSF: natural Sal forest site; -: indicates absent.

Species richness, species overlapping, similarity index and distribution pattern (%)

We observed that the highest species richness (n = 34) was recorded in the natural Sal forest site (Table 3). But in between the reforestation activities, the highest species richness (n = 14) was found in the woodlot plantation site than agroforestry site. The highest overlapping species (n = 6) were found in between agroforestry and woodlot followed by the similarity index in between agroforestry and natural Sal forest site (Table 3). Accordingly, the higher similarity index (41%) was found in agroforestry and woodlot plantation site than the agroforestry and natural Sal forest site. Most tree species (94%–100%) in the natural forest along two plantation activities had a contagious/clumped distribution pattern (Table 3), with only a few species having random distribution. The higher contagious distribution revealed that the most species having a low frequency.

Diversity indices (Shannon-Wiener index, Simpson index, Species evenness)

The highest Shannon-Wiener index (1.79) was found in agroforestry site and the lowest Shannon-Wiener (1.72) was recorded in woodlot plantation site followed by natural Sal forest site (Table 4). The highest Simpson index of the tree was found in the agroforestry site (0.79) followed by the woodlot plantation site (0.70) which was higher than the Simpson index of the natural Sal forest site (0.56) (Table 4). The species evenness of agroforestry site (0.60) was found higher than both of natural Sal forest (0.26) and woodlot plantation site (0.39) (Table 4). But Margalef’s index of natural Sal forest site (4.96) was the higher than other two plantation activities in the study area.

Table 4 . Diversity indices of the recorded tree species in the three sites of study area.

Diversity indicesAFWLNSF
Simpson index0.790.700.56
Margalef’s index1.441.964.96

AF: agroforestry site; WL: woodlot plantation site; NSF: natural Sal forest site.

Soil properties of three forest sites

The result of descriptive analysis (minimum, maximum, median, quartiles values) of all soil samples across three forest sites were shown in Figure 5. There was marked variability in levels of all the studied parameters with frequent outlier data (Fig. 6). We observed that at 0–15 cm soil depth, organic matter of soil was significantly higher in the natural Sal forest plots (2.47%) which is statistically similar to agroforestry plots (2.39%) than in woodlot plantations (2.06%) (Table 5). On the other hand, at 15–30 cm soil depth, organic matter content (1.67%) was higher in agroforestry site than in woodlot plantation site (1.58%) and natural Sal forest site (1.37%) in natural Sal forest site (Table 5). However, available P was significantly higher in agroforestry plots (62.67 µg g−1 and 30.40 µg g−1) at both soil depth relative to the other two forest types. No significant differences in exchangeable K was found among the three forest sites. The highest exchangeable K was in agroforestry site plots (0.36 meq/100 g), followed by the woodlot plantations (0.32 meq/100 g) and the natural Sal forest site (0.33 meq/100 g) at 0–15 cm soil depth (Table 5). But at 15–30 cm soil depth, the highest exchangeable potassium content (0.31 meq/100 g) was recorded in natural Sal forest site whereas exchangeable potassium content (0.24 meq/100 g) was found in agroforestry site.

Table 5 . Mean values and standard deviation of soil samples.

Forest sitesOM (%)Total N (%)Available P (µg g−1)Exchangeable K (meq/100 g)
0–15 cm15–30 cm0–15cm15–30 cm0–15 cm15–30 cm0–15 cm15–30 cm
AF2.39 ± 0.59a1.67 ± 0.55a0.14 ± 0.05a0.07 ± 0.03b62.67 ± 57.47a30.40 ± 32.51a0.36 ± 0.24a0.24 ± 0.08b
WL2.06 ± 0.59b1.58 ± 0.41a,b0.11 ± 0.02b0.10 ± 0.02a24.07 ± 30.31b21.09 ± 20.67b0.32 ± 0.07a0.25 ± 0.05b
NSF2.47 ± 0.47a1.37 ± 0.28b0.13 ± 0.02a0.06 ± 0.02b4.12 ± 2.59c1.51 ± 0.18c0.33 ± 0.07a0.31 ± 0.09a
p value0.00020.00250.00100.00000.00000.00000.37460.0000
F value9.026.217.1527.7437.7126.360.9919.82

Values are presented as mean ± standard deviation.

AF: agroforestry site; WL: woodlot plantation site; NSF: natural Sal forest site; OM: organic matter; N: nitrogen; P: phosphorus; K: potassium.

Statistical analysis was performed for soil properties at both soil depths in the study area. Different letters indicate significant differences (p = 0.05) across forest sites according to Turkey HSD (One-way ANOVA test).

Figure 6. Boxplot showing minimum, maximum, medians, quartiles values of all soil samples. (A, B) OM (%) at 0–15 cm and 15–30 cm. (C, D) Total N (%) at 0–15 cm and 15–30 cm. (E, F) Available P (µg g–1) at 0–15 cm and 15–30 cm. (G, H) Exchangeable K (meq/100 g) at 0–15 cm and 15–30 cm within the three sites. AF: agroforestry site; WL: woodlot plantation site; NSF: natural Sal forest site; OM: organic matter; N: nitrogen; P: phosphorus; K: potassium.

Tree species structure, composition and diversity of three forest sites

The present study revealed that the highest basal area (m2 ha−1) of tree species was found in natural Sal forest site. Similar result was found by Majumdar et al. (2014) where they recorded 16.36 m2 ha−1 of basal area in the natural forest site. The Sal forest is an old forest where trees have been grown for a long time. So, the natural Sal forest has a larger basal area than the plantation Sal forest. In the natural Sal forest site, trees are grown naturally and very young to giant trees are grown there without disturbing others. Whereas in the agroforestry and woodlot plantation, trees are felled off after a certain period of time and very young to medium trees are found there. Khan et al. (2011) recorded a very small number of trees in large-sized classes (50 cm to 70 cm dbh) Majumdar et al. (2014) reported the highest stem dispersion (> 50%) in young tree species (10–30 cm girth).

The highest IVI was also found for Shorea robusta under natural forest site but in agroforestry site, the highest IVI was also found for Acacia auriculiformis (96.86%). About 70%–75% of the trees in Madhupur Sal forests are Sal and highest IVI was also found in Shorea robusta (40.87) species (Malaker et al. 2010) and the lowest in Syzygium Salicifolium (1.08). Sal and Sinduri had the highest IVI, followed by Amloki and Sisoo reported by (Paul et al. 2015) in their study.

The present study inferred that the species richness of 1.8 ha investigated area (10 tree species in agroforestry site, 14 tree species in woodlot plantation plots and 34 tree species in natural Sal forest site) indicates the less tree species richness in Madhupur Sal forest. The tree species composition is comparatively lower than other natural forests in Bangladesh. Rahman et al. (2019) found a total of 66 tree species were growing within the natural forest patch. Hossain et al. (2015) found 107 tree species (72 genera and 37 families) from the Kamalachari Natural Forest of Chittagong South Forest Division; 135 species and 105 genera of 45 families were found in North central Eastern Ghats of India (Naidu et al. 2018). Nandy and Das (2013) found 35, 32, and 42 tree species in natural forests and 47, 37, and 48 in paan jhum agroforestry plantations in Barak valley, Northeast India. The poor tree species of Madhupur Sal forest may be attributed to land invasion, agricultural production, and illicit logging. That’s why participatory plantation programs like agroforestry and woodlot plantation under the umbrella of community or social forestry programs would be alternative to reforesting the degraded natural Sal forest region. The reason for getting the highest species-area curve in natural Sal forest site is that it harbors the different types of natural species. Behera et al. (2002) also found similar species-area curves in the coniferous and semi-coniferous forest in the Subansiri district, Arunachal Pradesh.

The Shannon-Wiener diversity index values from 1.72 to 1.76 of three forest sites which are similar to the findings of Tripathi et al. (2010); Borah et al. (2014); Sanou et al. (2018) that fall within the range (0.70–3.57). The Simpson dominance index for the agroforestry site revealed a high value, indicating that the agroforestry site is less consolidated and active from a functional standpoint. The authors reported that the reason for the higher species evenness in the agroforestry site in comparison to other sites is that trees are intensively cultivated to mitigate the local demand of the people. The highest Margalef’s index (4.96) was found in natural Sal forest plots which are similar to the findings of Kibria and Saha (2011). They observed that maximum margalef index (4.32) in natural forest because of natural forests have more species than agroforestry systems. It could be related to the farmer’s personal preferences for agroforestry plants. Nandy and Das (2013) explored that the most of the species in paan jhum agroforestry were more evenly distributed or contagiously distributed which comparable to this study.

Soil nutrient status of study sites

We found that organic matter of soil was highest in the natural Sal forest plots at topsoil (0–15 cm depth) (Table 5, Fig. 7A) which is statistically similar to agroforestry site. This contribution could be owing to high-quality litterfall, root biomass, increased potential carbon and other variables. Due to the accumulation of organic components, the topsoil of a natural forest site has more organic matter, which lowers the N and K concentrations (Fig. 7A, C). In terms of subsoil (15–30 cm soil depth), the agroforestry site had the highest organic matter (Table 5, Fig. 7D). Decomposed residues help to maintain the higher organic matter levels on agroforestry sites (Sharma et al. 2009). This may be owing to plant residues or fertilizer practices that raised subsoil N concentrations but decreased other nutrients. (Table 5, Fig. 7D–F). In the Madhupur Sal forest, reforestation initiatives like woodlot plantation and agroforestry boost the organic matter content of the subsoil. A similar result was observed by Mukul (2009) who found organic matter decreased with the conversion of natural forest into another land use at topsoil. Paudel and Sah (2006) reported that organic matter was found to be higher in the agroforestry plots (4.75%) than in adjacent forest plantations (3.18%) at topsoil Chowdhury et al. (2022) found that natural forest had the most organic matter (1.75%), followed by pineapple, lemon and banana agroforestry which supports the present study. The total nitrogen (%) was highest at topsoil in agroforestry plots which is similar to the findings of Kibria and Saha (2011) where pineapple agroforestry had the most nitrogen (0.09%), followed by lemon, banana, and natural forest. Chowdhury et al. (2022) reported that forest plantations had (0.15%) total N, compared to (0.10%) in slash-and-burn hills and agroforestry plots (0.08%). Hasan and Mamun (2015) reported that total N content was the highest (0.145%) in the plantation stand and the lowest (0.112%) in the mixed and pure stand, respectively. This may be a result of the planting of seasonal legume crops in the agroforestry plots, which may increase the soil’s nitrogen content. At both soil depths, the highest levels of P and K were found in agroforestry plots, intermediate in the woodlot plantation site, and lowest in the natural Sal forest site (Table 5, Fig. 7). The increase in P and K content during agroforestry practices could also be due to organic compost fertilization. A study demonstrated that long-term fertilization with cow dung increased the amount of accessible P and K in agroforestry plots (Singh et al. 2003). These nutrient concentrations are, of course, dependent on the decomposition of organic debris. Compared to other studies, a higher breakdown of organic matter in the soil leads to higher P and K concentrations (Haque et al. 2014; Mahmud et al. 2018). Kibria and Saha (2011) found that natural forest has the highest potassium (0.36 meq/100 g), followed by banana, pineapple, and lemon agroforestry (0.33, 0.28, and 0.25 meq/100 g). Our findings have supported the research of Sanou et al. (2018) and they reported that the phosphorus and potassium content of the highly disturbed site was statistically higher than a low, troubled site in the forest.

Figure 7. Relation between OM (%) with (A, D) Total N (%), (B, C) Available P (µg g–1) (C, F) Exchangeable K (meq/100 g) at both 0–15 cm and 15–30 cm depth in the three different land-use systems. Error bar indicates the standard error of the mean. AF: agroforestry site; WL: woodlot plantation site; NSF: natural Sal forest site; OM: organic matter; N: nitrogen; P: phosphorus; K: potassium.

Our results indicate that vegetation compositions are well in the woodlot plantation site, but biodiversity indices are rich in the agroforestry site. The soils in agroforestry plots and woodlot plantation sites contain more nutrients than natural Sal forest sites, with agroforestry providing greater advantages for soil fertility. The ecological and environmental balance of Madhupur Sal forest is destroyed by local people for their living and meeting the food demand. We suggest that agroforestry and woodlot plantation should be practiced to return the deforested land under green coverage and maintain the ecological balance. Our results indicate that reforestation activities are promising for sustainable land management in the Madhupur Sal forest regions. Therefore, Government and local non-governmental organizations (NGOs) should use public awareness campaigns and financial incentives to encourage the widespread use of agroforestry and woodlot plantation practices to limit forest encroachment in this natural Sal forest.

We would like to thank Bangladesh Agricultural University Research System (BAURES) for financial support and the authorities of Madhupur Sal Forest in Bangladesh for their invaluable assistance throughout data gathering.

DBH: Diameter at breast height

ANOVA: Analysis of variance

TFF: Tree Farming Fund

FD: Forest Department

AF: Agroforestry site

WL: Woodlot plantation

NSF: Natural Sal forest

MKH conceived the ideas, conducted field study, conducted the data collection, formal analysis, and wrote and reviewed the manuscript. He also secured the funding. MTI, RA, NAR conducted the data collection, reviewed the manuscript. All authors read and approved the final manuscript.

The authors affirm that the study’s data are in the manuscript and supplementary materials. The corresponding author can also provide raw data that support the study’s finding upon request.

  1. Alam M, Furukawa Y, Sarker SK, Ahmed R. Sustainability of Sal (Shorea robusta) forest in Bangladesh: past, present and future actions. Int For Rev. 2008;10(1):29-37.
  2. Alam MK. Diversity in the woody flora of Sal (Shorea robusta) forests of Bangladesh. Bangladesh J For Sci. 1995;24(1):41-51.
  3. Bangladesh Forest Department (BFD). Ministry of Environment and Forest, Government of the People's Republic of Bangladesh, Dhaka, Bangladesh; 2017 [Accessed 20 Jun 2022].
  4. Behera MD, Kushwaha SPS, Roy PS, ivastava S Sr, Singh TP, Dubey RC. Comparing structure and composition of coniferous forests in Subansiri district, Arunachal Pradesh. Curr Sci. 2002;82(1):70-6.
  5. Borah N, Athokpam FD, Garkoti SC, Das AK, Hore DK. Structural and compositional variations in undisturbed and disturbed tropical forests of Bhuban hills in south Assam, India. Int J Biodivers Sci Ecosyst Serv Manag. 2014;10(1):9-19.
  6. Chowdhury FI, Barua I, Chowdhury AI, Resco de Dios V, Alam MS. Agroforestry shows higher potential than reforestation for soil restoration after slash-and-burn: a case study from Bangladesh. Geol Ecol Landsc. 2022;6(1):48-54.
  7. Chowdhury MA, Islam KN, Hafiz N, Islam K. Diversity of trees in a community managed forest: the case of Komolchori VCF, Khagrachari, Bangladesh. Geol Ecol Landsc. 2019;3(2):95-103.
  8. Dallmeier F, Kabel M, Rice R. Methods for long-term biodiversity inventory plots in protected tropical forests. In: Dallmeier F, editor. Long-term monitoring of biological diversity in tropical forest areas: methods for establishment and inventory of permanent plots. Paris: UNESCO; 1992. p. 11-46.
  9. Gain P. The last forests of Bangladesh. 2nd ed. Dhaka: Society for Environment and Human Development; 2002. p. 101-79.
  10. Haque SSM, Gupta SD, Miah S. Deforestation effects on biological and other important soil properties in an upland watershed of Bangladesh. J For Res. 2014;25(4):877-85.
  11. Hasan MK, Islam MT, Roshni NA, Hemel SAK. Effects of forest encroachment on tree stock parameters and soil nutrient status in the Madhupur Sal (Shorearobusta C.F. Gaertn) forest of Bangladesh. J Agric Food Environ. 2020;1(2):35-40.
  12. Hasan MK, Mamun MB. Influence of different stands of sal (Shorea robusta C. F. Gaertn.) forest of Bangladesh on soil health. Res Agric Livest Fish. 2015;2(1):17-25.
  13. Hossain MA, Hossain MK, Alam MS, Uddin M. Composition and diversity of tree species in Kamalachari natural forest of Chittagong South Forest Division, Bangladesh. J For Environ Sci. 2015;31(3):192-201.
  14. Islam KK, Gomes J, Toppo A, Biswas B, Mankin A, Paul A, et al. Enhancing livelihood and biodiversity through Caritas intervened project in the northeastern region of Bangladesh: a case study. J Agrofor Environ. 2022;15(1):1-9.
  15. Islam KK, Hoogstra M, Ullah MO, Sato N. Economic contribution of participatory agroforestry program to poverty alleviation: a case from Sal forests, Bangladesh. J For Res. 2012;23(2):323-32.
  16. Islam KK, Rahman GM, Fujiwara T, Sato N. People's participation in forest conservation and livelihoods improvement: experience from a forestry project in Bangladesh. Int J Biodivers Sci Ecosyst Serv Manag. 2015;9(1):30-43.
  17. Islam KK, Sato N. Participatory forestry in Bangladesh: has it helped to increase the livelihoods of Sal forests-dependent people? South For J For Sci. 2012;74(2):89-101.
  18. Islam KN, Rahman MM, Jashimuddin M, Hossain MM, Islam K, Faroque MA. Analyzing multi-temporal satellite imagery and stakeholders' perceptions to have an insight into how forest co-management is changing the protected area landscapes in Bangladesh. For Policy Econ. 2019;101:70-80.
  19. Jaccard P. The distribution of the flora in the alpine zone. New Phytol. 1912;11(2):37-50.
  20. Jackson ML. Soil chemical analysis. Englewood Cliffs: Prentice-Hall Inc.; 1958. p. 183-204.
  21. Khan N, Ahmed M, Shaukat SS, Wahab M. Siddiqui MF. Structure, diversity, and regeneration potential of Monotheca buxifolia (Falc.) A. DC. dominated forests of Lower Dir District, Pakistan. Front Agric China. 2011;5(1):106-21.
  22. Khan SI, Naher H. Breeding biology of the Red-Whiskered Bulbul, Pycnonotus Jocosus (Linnaeus, 1758) in Madhupur National Park, Bangladesh. J Asiat Soc Bangladesh Sci. 2020;46(2):179-89.
  23. Kibria MG, Saha N. Analysis of existing agroforestry practices in Madhupur Sal forest: an assessment based on ecological and economic perspectives. J For Res. 2011;22:533.
  24. Local Forest Office. Madhupur National Park. Dhaka: Bangladesh forest Division; 2013.
  25. Magurran AE. Ecological diversity and its measurement. Princeton: Princeton University Press; 1988. p. 145-6.
  26. Mahmud AA, Rahman MM, Hossain MK. The effects of teak monoculture on forest soils: a case study in Bangladesh. J For Res. 2018;29(4):1111-20.
  27. Majumdar K, Shankar U, Datta BK. Trends in tree diversity and stand structure during restoration: a case study in fragmented moist deciduous forest ecosystems of Northeast India. J Ecosyst. 2014;2014:845142.
  28. Malaker JC, Rahman MM, Azad-Ud-Doula Prodhan AKM, Malaker SK, Khan MAH. Floristic composition of Madhupur Sal forest in Bangladesh. J Soil Nat. 2010;4(1):25-33.
  29. Margalef R. Information theory in ecology. Gen Syst. 1958;3:36-71.
    Pubmed CrossRef
  30. Masum KM, Islam MN, Saha N, Hasan MZ, Mansor A. Assessment of land grabbing from protected forest areas of Bhawal National Park in Bangladesh. Landsc Res. 2016;41(3):330-43.
  31. Misra R. Ecology workbook. Calcutta: Oxford and IBH Publishing; 1968.
  32. Muhammed N, Haque F, Koike M. The role of participatory social forestry in the enhancement of the socio-economic condition of the rural poor: a case study of Dhaka forest division in Bangladesh. For Trees Livelihoods. 2008;18(4):395-418.
  33. Mukul SA. Ecological trade off between agroforestry and biodiversity: a case study from conservation area of Bangladesh [PhD dissertation]. Sylhet: Shahjalal University of Science & Technology; 2009.
  34. Naidu MT, Premavani D, Suthari S, Venkaiah M. Assessment of tree diversity in tropical deciduous forests of Northcentral Eastern Ghats, India. Geol Ecol Landsc. 2018;2(3):216-27.
  35. Nandy S, Das AK. Comparing tree diversity and population structure between a traditional agroforestry system and natural forests of Barak valley, Northeast India. Int J Biodivers Sci Ecosyst Serv Manag. 2013;9(2):104-13.
  36. Page AL, Keeney DR, Miller RH. Methods of soil analysis. Part 2: chemical and microbiological properties. 2nd ed. Madison: American Society of Agronomy; 1982.
  37. Paudel A, Bhattarai A, Yadav PK. Soil conservation practices in forest of Nepal. J Clean WAS. 2021;5(2):73-7.
  38. Paudel S, Sah JP. Physiochemical characteristics of soil in tropical sal (Shorea robusta Gaertn.) forests in eastern Nepal. Himal J Sci. 2006;1(2):107-10.
  39. Paul A, Mian M, Khan M, Islam M. Study on biodiversity conservation practice in Madhupur Sal Forest, Bangladesh. J Environ Sci Nat Resour. 2015;6(1):187-93.
  40. Rahman M, Nishat A, Vacik H. Anthropogenic disturbances and plant diversity of the Madhupur Sal forests (Shorea robusta C.F. Gaertn) of Bangladesh. Int J Biodivers Sci Manag. 2009;5(3):162-73.
  41. Rahman MM, Rahman MM, Guogang Z, Islam KS. A review of the present threats to tropical moist deciduous sal (Shorea robusta) forest ecosystem of central Bangladesh. Trop Conserv Sci. 2010;3(1):90-102.
  42. Rahman MM, Vacik H. Vegetation analysis and tree population structure of Sal (Shorea robusta C.F. Gaertn) forests: a case study from the Madhupur and Bhawal National Park in Bangladesh. In: Farina O, Polisciano G, editors. National parks: vegetation, wildlife and threats. New York: Nova Science Publishers; 2010. p. 193-206.
  43. Rahman MR, Hossain MK, Hossain MA. Diversity and composition of tree species in Madhupur National Park, Tangail, Bangladesh. J For Environ Sci. 2019;35(3):159-72.
  44. Rana MA, Toshikuni N, Muhammed NUR. Impact of Participatory Forest Management (PFM) on socio-economic development in Bangladesh: a case study in the Madhupur Sal Forest. J For Econ. 2007;53(1):46-56.
  45. Salam MA, Noguchi T. On sustainable development of social forestry in Bangladesh: experiences from Sal (Shorea robusta) forests. Environ Dev Sustain. 2005;7(2):209-27.
  46. Sanou L, Zida D, Savadogo P, Thiombiano A. Comparison of aboveground vegetation and soil seed bank composition at sites of different grazing intensity around a savanna-woodland watering point in West Africa. J Plant Res. 2018;131(5):773-88.
    Pubmed CrossRef
  47. Shannon CE, Weaver W. The mathematical theory of communication. Urbana: University of Illinois Press; 1963. p. 117.
  48. Sharma KL, Raju KR, Das SK, Prasad Rao BRC, Kulkarni BS, inivas K Sr, et al. Soil fertility and quality assessment under tree-, crop-, and pasture-based land-use systems in a rainfed environment. Commun Soil Sci Plant Anal. 2009;40(9-10):1436-61.
  49. Shukla RS, Chandel PS. Plant ecology and soil science. 9th ed. New Delhi: S. Chand & Company Limited; 2000. p. 121-376.
  50. Simpson E. Measurement of diversity. Nature. 1949;163:688.
  51. Singh J, Bora IP, Baruah A, Hussain M. Effect of shifting cultivation on nutrient status of soil in Silonijan (Karbi-Anglong) Assam. Indian For. 2003;129(11):1329-38.
  52. Tripathi OP, Upadhaya K, Tripathi RS, Pandey HN. Diversity, dominance and population structure of tree species along fragment-size gradient of a subtropical humid forest of Northeast India. Res J Environ Earth Sci. 2010;2(2):97-105.
  53. Walkley A, Black IA. An examination of the Degtjareff method for determining soil organic matter, and a proposed modification of the chromic acid titration method. Soil Sci. 1934;37(1):29-38.
  54. Whitford PB. Distribution of woodland plants in relation to succession and clonal growth. Ecology. 1949;30(2):199-208.
  55. Zheng H, Chen F, Ouyang Z, Tu N, Xu W, Wang X, et al. Impacts of reforestation approaches on runoff control in the hilly red soil region of Southern China. J Hydrol. 2008;356(1-2):174-84.

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