Research Article

Phytosociological Analysis of Moist Temperate Forest in Shah Pur, District Shangla

Sami ul Haq, Basheer Ahmad* and Bilal Ahmed Qazi

Pakistan Forest Institute, Peshawar, Khyber Pakhtunkhwa, Pakistan

Received | May 17, 2024; Accepted | June 20, 2024; Published | June 27, 2024

*Correspondence | Basheer Ahmad, Pakistan Forest Institute, Peshawar, Khyber Pakhtunkhwa, Pakistan; Email: [email protected]

Citation | Haq, S., B. Ahmad and B.A. Qazi. 2024. Phytosociological analysis of moist temperate forest in Shah Pur, District Shangla. Pakistan Journal of Forestry, 74(1): 40-48.

DOI | https://dx.doi.org/10.17582/journal.PJF/2024/74.1.40.48

Keywords | Phytosociology, Species composition, Edaphic factors, Shanon’s Index, Simpson index, Biodiversity

Copyright: 2024 by the authors. Licensee ResearchersLinks Ltd, England, UK.

This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).

Introduction

Vegetation is a unit which possesses characteristic physiognomic structure which differentiates it from other such units (Hussain and Ilahi, 1991). Environmental gradients, such as topography and soil variables, shape vegetation structure (Ismail et al., 2019; Khadanga and Jayakumar, 2020). Altitude plays a significant role in shaping vegetation types and diversity, influenced by temperature gradients (Mani, 1978). This, in turn, affects the temperature gradient, which plays a crucial role in shaping vegetation patterns, diversity, and distribution (Heaney and Proctor, 1989; Tanner et al., 1998; Vazquez and Givnish, 1998). Understanding these dynamics is crucial for managing forest ecosystems.

Braun-Blanquet et al (1915) defined the plant community as a group of plants having characteristic species and a stability to the prevailing environment (Podani, 2006). The plant community of a region is a function of many factors such as time, altitude, slope, latitude, aspect, rainfall, soil composition and humidity, all of which play a role in its formation and composition (Kharkwal et al., 2005). The dynamics of plant species development and decline reshape the composition and distribution of species within communities (Watt, 1964). Plant communities undergo seasonal fluctuations and successional changes in response to heat, moisture, and light, influenced by the vegetation itself (Heady, 1958).

Forest ecosystems exhibit variations in structure, composition, and function in response to environmental and anthropogenic factors (Gairola et al., 2008; Timilsina et al., 2007). Habitat variation, time and biotic interactions determine the distribution of individuals of the same and different plant species in a community (Khan et al., 2013). These variations are correlated with geographical location, productivity, evolutionary competition, and human-forest interactions (Eriksson, 1996; Criddle et al., 2003).

Phytosociology, a scientific discipline, focuses on studying plant communities, encompassing their composition, development, and interrelationships among species (Mishra et al., 2012). This field examines vegetation’s composition, structure, development, and distribution (Tansley, 1920). Phytosociological analysis serves as a valuable tool for elucidating population trends of individual plant species and comprehending their interrelationships with coexisting species. Phytosociologists employ multivariate statistical techniques to understand vegetation structure and its responses to environmental effects (Ahmad et al., 2019; Dufrêne and Legendre, 1997).

Phytosociology provides a framework to categorize and classify ecological groupings, helping understand plant communities’ ecological relationships and the influence of various factors on their organization (Kolasa and Rollo, 1991; Legendre and Fortin, 1989). Oosting (1956) emphasized the importance of phytosociological parameters in understanding spatial patterns and sociological behavior of plants.

Effective forest management requires understanding phytosociological parameters, including diversity indices, species richness, and distribution patterns (Kumar, 2010). Analyzing these parameters provides insights into community relationships and resilience to environmental changes (Magurran, 1988). Indicator species play a crucial role in classifying plant associations and predicting species richness across environments (Dufrêne and Legendre, 1997). These indicators are valuable for monitoring changes in plant communities resulting from environmental or management modifications (Iqbal et al., 2018; Rahman et al., 2020).

This research project has two primary objectives. First, it aims to study the phytosociology and species diversity of the moist temperate forest in the Shahpur Valley, Shangla District. This entails examining the composition, structure, and distribution patterns of plant communities in this distinctive ecosystem. second, this research seeks to identify the soil factors that influence the formation and dispersion of plant communities in the area. By understanding the relationship between soil characteristics and plant distribution, this study will inform evidence-based ecosystem management and conservation strategies in the region.

Materials and Methods

Located in Pakistan’s Khyber Pakhtunkhwa province Shangla District, spans an area of approximately 1,586 square kilometers and comprising 28 union councils. Shangla District is located between 33.08° N to 34.31° N latitude and 72.33° E to 73.01° E longitude.

Shangla District is Bounded by Kohistan District to the north, Battagram District to the east, Swat District to the west, and Buner District to the south and also encompasses the Kala Dhaka, or Black Mountain of Hazara, in the east. Shangla District is distinguished by its picturesque valleys nestled among rolling hills and enveloped by forested mountains, hosting coniferous forests with trees like Picea smithiana, Cedrus deodara, Pinus wallichiana, and Abies pindrow. Shangla District,s rugged terrain is characterized by high mountains, steep valleys, and an average elevation ranging from 5,900 to 12,000 feet above sea level (Alpuri Forest Division Working Plan).

 

Material

In this research project, various instruments and methodologies were utilized for field data collection. The field data collection instruments employed included Global Positioning System GPS for recording geographical coordinates and elevation data, a clinometer for measuring slope percentages, and a soil auger for collecting soil samples. The collected data subsequently analyzed using software such as including Microsoft Excel and R software.

The field data collection in the Shahpur Area of Shangla District was conducted using systematic and randomized sampling procedures to ensure representativeness and accuracy. For the purpose of this study, the Shahpur Valley was divided into two distinct blocks, Kana East and Kana West, with respective forested areas of 2,060 acres and 2,970 acres. To determine the sampling intensity, the sample area was calculated as 0.1% of the total forest area (5,030 acres). For Kana East, this resulted in 20 sample plots, each measuring 0.1 acre. Kana West, on the other hand, had 30 sample plots of the same size.

The Shahpur Valley comprised a total of 50 sample plots combining Kana East and Kana West Blocks. The standard plot size was approximately 0.1 acres, corresponding to either a circular plot with an 11-meter radius or a 20 x 20-meter square, facilitating efficient data collection.

A stratified random sampling approach was employed, selecting plots from lower elevations to the tree line, to ensure representation across key factors: Tree population structure, diameter at breast height (DBH), density, species composition, altitude, and slope aspect.

Soil samples were systematically collected from plots showcasing notable species diversity and variation, and were subsequently submitted to laboratory analysis for physical, chemical, and biological characterization. A comprehensive soil analysis was conducted, assessing five key parameters: Moisture content was determined by measuring the difference between fresh weight and oven-dry weight, expressed as a percentage. Ash content was calculated based on the weight loss during ashing, soil organic carbon determined by multiplying the ash content by 0.58.

pH and electrical conductivity (EC) were determined using a soil-to-water suspension, prepared by mixing of air-dried soil with distilled water, shaking for 30 minutes, and measuring with a calibrated pH meter and conductivity probe. These rigorous and systematic methods and analyses were employed to collect high-quality data, providing valuable insights and informing research conclusions.

Results and Discussion

Figure 2 depicts the species composition percentages of sampled plots within the moist temperate forest of Shahpur Valley in Shangla. The sampled tree species encompass both broadleaves and conifers.

 

Table 1: Shannon’s and Simpson’s diversity value of each plots.

Plot no	Shannon value	Simpson value
1	0.87	0.60
2	0.89	0.52
3	0.89	0.52
4	0.84	0.48
5	0.69	0.50
6	1.00	0.60
7	0.93	0.54
8	1.04	0.63
9	0.64	0.44
10	0.99	0.60
11	0.62	0.43
12	1.30	0.71
13	0.97	0.59
14	1.09	0.66
15	1.49	0.75
16	1.06	0.64
17	1.03	0.62
18	1.14	0.60
19	1.36	0.74
20	1.03	0.62
21	1.26	0.68
22	0.57	0.39
23	0.61	0.42
24	0.69	0.50
25	0.00	0.00
26	0.51	0.33
27	1.09	0.62
28	0.50	0.32
29	1.54	0.78
30	1.36	0.74
31	0.27	0.12
32	0.33	0.18
33	1.35	0.73
34	0.00	0.00
35	1.01	0.54
36	1.35	0.73
37	1.18	0.64
38	0.93	0.54
39	1.00	0.61
40	0.00	0.00
41	0.41	0.20
42	0.85	0.43
43	0.73	0.41
44	0.56	0.38
45	0.43	0.26
46	1.06	0.64
47	0.89	0.52
48	0.38	0.22
49	0.68	0.49
50	1.27	0.65

 

In ecology, d iversity ind ex is im po rtant param eter intende d to measu rem ent of biodiversi ty within an ecosystem Two basic st atistic al tools ecologists use to quantify dive rsity of species, S hannon’s and Simpson’s diversit y indices, Sh annon-Wie ner divers ity index has been u sed exten sively in environmental studies to estimate the species ric hness an d ecosystem s abu ndance. The index works using very well under comparative situations; where one is comparing two or more environments simultaneously (Omayio and Mzungu, 2019).

 

Tale 2: Shannon’s diversity value classes.

Classes values	Count	Range
Zero	3	0-1.54
0 To 1	28
Above 1	19

 

Shannon’s diversity index values ranged from 0 to 1.54. Classes with a value of 0 indicated no diversity, which was observed in three classes. Moderate diversity (values between 0 and 1) was found in 28 plots, while 19 plots exhibited high diversity (values above 1).

 

Table 3: Simpson’s diversity value class.

Class values	Count	Range
Zero value	3	0-0.78
Above zero	47

 

Simpson’s diversity values range from 0 to 0.78. A value of zero indicates low diversity, while a value of 0.78 signifies high diversity.

 

Figure 3 canonical correspondence analysis (CCA) biplot illustrating the relationships between 22 plant species and key environmental variables. In a CCA figure, the longer the arrow line, the more influential or explanatory the environmental factor is. In a CCA biplot, the angle between the arrow lines represents the correlation between environmental factors, where smaller angles indicate positive correlations, right angles (90°) indicate no correlation, and larger angles indicate negative correlations.

The data indicates that Pinus wallichiana is the predominant species in the area, comprising 53% of the total species. The remaining species distribution is Quercus dilatata (9%), Quercus incana (8%). Both Picea smithiana and Robinia pseudocacia had a 4% record. Salix alba and Diospyros make up 3% of the total. Each of the following species makes up 2% of the total species: Populus nigra, Juglans regia, and Ailanthus altisimia. The remaining 10% are made up of various others species.

 

 

The graph illustrates the soil pH levels for representative plots, ranging from 6.9 to 7.6 on a scale of 0 (most acidic) to 14 (most alkaline), with 7 as neutral. Most plots (majority) exhibit slightly acidic to neutral pH values (7-7.4). Plots 2, 15, 19, and 43 are slightly alkaline, with higher pH values. Plot 42 has a pH of 7.1, nearing neutrality.

Soil moisture content varied significantly across plots, ranging from 1.2% (plots 18 and 43) to 17.1% (plot 14). Most plots had mid-range values (2.1-5.4%). Local conditions, soil type, and recent weather drove these differences.

The Figure 6 displays the electrical conductivity (EC) values of soil samples from various plots, measuring the soil’s ability to conduct electrical current and indicating salinity or ion concentration. EC values range from highest: Plot 14 (7.46 dS/m), lowest: plot 6 (3.73 dS/m) and mid-range: 3.2-5.44 dS/m (remaining plots). Higher EC values, like Plot 14’s, suggest increased salt concentrations potentially harmful to plant growth. In contrast, Plot 6’s lower EC indicates relatively lower salt levels. EC values are typically measured in dS/m or mS/cm.

 

 

Figure 7 presents the organic carbon content (O. carbon) in soil samples from various plots, expressed as a percentage. Organic carbon indicates the presence of decomposed plant and animal materials, reflecting soil organic matter. Highest O. carbon: Plot 14 (9.17%), Lowest O. carbon: Plots 1 (1.25%), 2 (1.43%), and 43 (1.31%) and Mid-range O. carbon: 2.1-4.6% (remaining plots). Plot 14’s high organic carbon content suggests fertile soil with enhanced moisture retention and Improved nutrient capacity. In contrast, plots 1, 2, and 43 require organic matter enhancements or targeted soil management practices due to their low organic carbon levels.

Iqbal et al. (2014) studied the vegetation of pine forests of Shangla District of Khyber Pakhtunkhwa Province of Pakistan is described. This study selected 30 stands across different locations, where gymnospermic species were found to be widely distributed and dominant in each stand. Sampling was conducted using the point-centered quarter (PCQ) method. Pinus wallichiana showed the highest density of 409 trees ha-1, with a basal area of 132.1 m2 ha-1, in 26 out of the 30 sampled stands. Abies pindrow exhibited moderate abundance, occurring in 7 stands with a density of 384 trees ha-1 and basal area of 145.3 m2 ha-1, whereas Picea smithiana was scarce, recorded from just 2 sites. The results indicate that young stands had a significantly higher population density compared to mature stands. Our study revealed that the moist temperate forest of Shahpur Valley, Shangla District, exhibits a unique species composition, with Pinus wallichiana emerging as the dominant species, accounting for 53% of the total species. Quercus dilatata and Quercus incana follow, contributing 9% and 8%, respectively. Picea smithiana and Robinia pseudocacia both make up 4%, while Salix alba and Diospyros account for 3%. Populus nigra, Juglans regia, and Ailanthus altissima each constitute 2% of the total species composition.

Ismail and Elawad (2015) conducted a comprehensive study to assess plant diversity across 14 selected vegetation sites. They employed the Shannon index, a widely used metric, to quantify species diversity.

Species richness varied across the 14 studied sites, with the highest number of species (19) recorded at Site 2.The highest values for the Shannon diversity index and evenness index were recorded at Site 12. Sites 9 and 10 showed the highest similarity (73.39%), whereas sites 1 and 3 exhibited the lowest similarity (41.83%). Our study’s assessment of Shannon’s and Simpson’s diversity indices revealed that most forest plots exhibit moderate to high diversity levels, indicating a healthy and resilient ecosystem. The Shannon diversity index values ranged from 0 to 1.54, while Simpson’s diversity index values ranged from 0 to 0.78.

According to (Khan et al., 2016), the Indus Kohistan valley hosts seven tree species in its pine communities. The study found that the Pinus wallichiana was recorded at 23 locations, with the second-highest mean importance value while Cedrus deodara, recorded at 28 locations, exhibited the highest mean importance value. According to the study, Picea smithiana was recorded at eight locations in the Indus Kohistan valley, achieving the fourth-highest importance value. It was the dominant species in one stand. It ranked as the second dominant species in four stands. Abies pindrow was the third most frequent species and correspondingly attained the third-highest mean importance value. Pinus gerardiana, Quercus baloot, and Taxus fuana were the rarest species in the region, characterized by notably low mean importance values. Cedrus deodara was dominant in four monospecific stands and was also present in six mixed-species communities.

The Cedrus-Pinus community was the most widespread, occurring in 13 stands. The Abies-Pinus wallichiana community, found in six locations, was the second-most frequent community in the research area. Notably, it occurred at twice as many locations as the combined total of the Cedrus-Picea and Abies-Picea communities.The communities of Pinus wallichiana, Picea, and Cedrus-Pinus gerardiana were localized, each occurring in only one location.

Our study revealed that the moist temperate forest of Shahpur Valley, District Shangla, harbors a diverse array of 22 tree species. The species composition is characterized by Pinus wallichiana (53%): dominant species, Quercus dilatata (9%) and Quercus incana (8%): secondary dominants, Picea smithiana and Robinia pseudocacia (4% each), Salix alba and Diospyrus lotus (3% each), Populus nigra, Juglans regia, and Ailanthus altissima (2% each).

Shaheen et al. (2012) surveyed to investigate to assess the diversity of moist temperate forests in the western Himalayas, specifically focusing on the Bagh district Kashmir. As the Simpson’s Diversity Index varied from 0.75 to 2.27, while Shannon’s Evenness index ranged from 0.21 to 0.71. Our study assessment of Shannon’s and Simpson’s diversity indices reveals that the majority of the forest plots exhibit moderate to high diversity, indicative of a healthy environment. Shannon’s diversity values range from 0 to 1.54 and Simpson’s Diversity values range from 0 to 0.78.

Conclusions and Recommendations

The moist temperate forest of Shahpur Valley exhibits a unique species composition, dominated by Pinus wallichiana (53%), followed by Quercus dilatata (9%) and Quercus incana (8%). Other notable species include Picea smithiana, Robinia pseudocacia (4% each), Salix alba, Diospyros (3% each), and Populus nigra, Juglans regia, Ailanthus altissima (2% each). Diversity indices show moderate to high diversity (Shannon’s: 0-1.54, Simpson’s: 0-0.78), indicating a healthy environment. Key soil factors influencing species distribution are pH (7.38), electrical conductivity (4.67 μS/cm), moisture content (2.73%), and organic carbon (2.08%). The study highlights the prevalence of coniferous forests, with Pinus wallichiana as the predominant coniferous species. These findings have significant implications for developing effective conservation and management strategies tailored to Shahpur Valley’s unique ecological characteristics.

Novelty Statement

A study in Shahpur Valley, District Shangla, revealed its unique conifer-dominated biodiversity. These findings will inform targeted conservation and management strategies to protect the valley’s distinct ecological features.

Author’s Contribution

Bilal Ahmed Qazi: Conceptualization, Investigation.

Basheer Ahmad: Wrote the draft and reviewed.

Samiul Haq: Data curation and editing.

Conflict of interest

The authors have declared no conflict of interest.

References

Ahmad, Z., Khan, S.M., Abd_Allah, E.F., Alqarawi, A.A. and Hashem, A., 2016. Weed species composition and distribution pattern in the maize crop under the influence of edaphic factors and farming practices: A case study from Mardan, Pakistan. Saudi J. Biol. Sci., 23(6): 741–748. https://doi.org/10.1016/j.sjbs.2016.07.001

Ahmad, Z., Khan, S.M., Ali, M.I., Fatima, N. and Ali, S., 2019. Pollution indicandum and marble waste polluted ecosystem; role of selected indicator plants in phytoremediation and determination of pollution zones. J. Cleaner Prod., 236: 117709. https://doi.org/10.1016/j.jclepro.2019.117709

Braun-Blanquet, J., Conard, H.S. and Fuller, G.D., 1915. Plant sociology: the study of plant communities. New York: McGraw-Hill.

Dufrêne, M. and Legendre, P., 1997. Species assemblages and indicator species: the need for a flexible asymmetrical approach. Ecol. Monogr., 67(3): 345–366. https://doi.org/10.1890/0012-9615(1997)067[0345:SAAIST]2.0.CO;2

Eriksson Regional dynamics of plants: review of evidence for remnant, source-sink and meta-populations ,Oikos, (1996).

Gairola, S., Rawal, R.S. and Todaria, N.P., 2008. Forest vegetation patterns along an altitudinal gradient in sub-alpine zone of west Himalaya, India. Afr. J. Plant Sci., 2(6): 42–48.

Heady, H.F., 1958. Vegetational changes in the California annual type. Ecology, 39: 402–616. https://doi.org/10.2307/1931750

Heaney, A. and Proctor, J., 1989. Chemical elements in fitter at a range of altitude on Volcan barva, Costa Rica. In: Proctor J (ed) nutrients in tropical forest and Sawanna ecosystems. Blackwell Scientific Publications, Oxford, pp. 255–271.

Hussain, F. and Ilahi, I., 1991. Ecology and vegetation of lesser Himalayas, Pakistan. Department of Botany, University of Peshawar. pp. 187.

Iqbal, J., Ahmed, M., Khan, A. and Siddiqui, F.M., 2014. Vegetation description of some pine forests of Shangla District of Khyber Pakhtunkhwa Pakistan. A preliminary study. J. Biol., 4(1): 83–88.

Iqbal, M., Khan, S.M., Khan, M.A., Ahmad, Z. and Ahmad, H., 2018. A novel approach to phytosociological classification of weeds flora of an agro-ecological system through cluster, two way cluster and indicator species analyses. Ecol. Indic., 84: 590–606. https://doi.org/10.1016/j.ecolind.2017.09.023

Ismail, A.H., Lim, C.C. and Omar, W.M.W., 2019. Evaluation of spatial and temporal variations in zooplankton community structure with reference to water quality in Teluk Bahang Reservoir, Malaysia. Trop. Ecol., 60(2): 186-198. https://doi.org/10.1007/s42965-019-00023-2

Ismail, I.M. and Elawad, A.A., 2015. Phytosociological analysis and species diversity of herbaceous. Jordan J. Biol. Sci., 8(2): 151–157. https://doi.org/10.12816/0027562

Khadanga, S.S. and Jayakumar, S., 2020. Tree biomass and carbon stock: Understanding the role of species richness, elevation, and disturbance. Trop. Ecol., 61(1): 128. https://doi.org/10.1007/s42965-020-00070-0

Khan, A., Ahmed, M., Siddiqui, M.F., Iqbal, J. and Wahab, M., 2016. Phytosociological analysis of pine forest at Indus Kohistan, KPK, Pakistan. Pak. J. Bot., 48(2): 575–580.

Khan, S.M., Page, S., Ahmad, H. and Harper, D., 2013. Identifying plant species and communities across environmental gradients in the Western Himalayas: Method development and conservation use. Ecol. Inform., 14: 99-103. https://doi.org/10.1016/j.ecoinf.2012.11.010

Kharkwal, G., Mehrotra, P., Rawat, Y.S. and Pangtey, Y.P.S., 2005. Phytodiversity and growth form in relation to altitudinal gradient in the Central Himalayan (Kumaun) region of India. Curr. Sci., 89: 873–878.

Kolasa, J. and Rollo, C.D., 1991. Introduction: The heterogeneity of heterogeneity: A glossary. Ecol. Heterogen, Springer. pp. 1–23. https://doi.org/10.1007/978-1-4612-3062-5_1

Kumar, J.I.N., Kumar, R.N., Bhoi, R.K. and Sajish, P.R., 2010. Tree species diversity and soil nutrient status in three sites of tropical dry deciduous forest of western India. Trop. Ecol., 51(2): 273-279.

Legendre, P. and Fortin, M.J., 1989. Spatial pattern and ecological analysis. Vegetation, 80: 107–138. https://doi.org/10.1007/BF00048036

Omayio , D . and Mzungu , E. (2019 ). Modification of Shannon -Wiener Diversity Index towards Quantitative Estimation of Environmental Wellness and Biodiversity Levels under a Non-comparative Scenario . J. Environ. Earth Sci., 9 (9): 46-57.

Magurran, A.E., 1988. Ecological diversity and measurement. Princeton University Press, Princeton. https://doi.org/10.1007/978-94-015-7358-0

Malik, Z.H., 1986. Phytosociological studies on the vegetation of Kotli Hills, Azad Kashmir, M. phil Thesis. University of Peshawar.

Mishra, N.K., Singh, R. and Ojha, S., 2012. Phytosociological perspectives of representative herbaceous genera of common occurrence belonging to family asteraceae in grassland ecosystem of Anpara Region in district Sonebhadra (UP). Indian J. Life Sci., 2(1): 119–123.

Eriksson, O., 1996. Regional dynamics of plants: Review of evidence for remnant, source-sink and meta-populations, Oikos, https://doi.org/10.2307/3546063

Oosting, H.J., 1956. The study of plant communities: An introduction of Plant Ecology (2nd edition).

Podani, J., 2006. Braun-Blanquet’s legacy and data analysis in vegetation science. J. Veg. Sci., 17: 113-117. https://doi.org/10.1111/j.1654-1103.2006.tb02429.x

Criddle, R.S., Church, J.N., Smith, B.N. and Hansen, L.D. 2003. Fundamental causes of the global patterns of species range and richness Russ. J. Plant Physiol.,

Rahman, A.U., Khan, S.M., Saqib, Z., Ullah, Z., Ahmad, Z., Ekercin, S., Mumtaz, A.S. and Ahmad, H., 2020. Diversity and abundance of climbers in relation to their hosts and elevation in the monsoon forests of Murree in the Himalayas. https://doi.org/10.30848/PJB2020-2(17)

Mani, S., 1978. Ecology and phytogeography of the high altitude plants of the Northwest Himalaya.

Shaheen, H., Ullah, Z., Mulk, S. and Harper, D.M., 2021. Authors personal copy forest ecology and management species composition and community structure of western Himalayan moist temperate forests in Kashmir.

Tanner, E.V.J., Vitousek, P.M. and Cuevas, E., 1998. Experimental investigation of nutrient limitation of forest growth on wet tropical mountains. Ecology, 79: 10–22. https://doi.org/10.1890/0012-9658(1998)079[0010:EIONLO]2.0.CO;2

Tansley, A.G., 1920. The classification of vegetation and the concept of development. J. Ecol., pp. 118–149. https://doi.org/10.2307/2255529

Timilsina, N., Ross, M.S. and Heinen, J.T., 2007. A community analysis of Sal (Shorea robusta) forests in the western Terai of Nepal. For. Ecol. Manage., 241(1–3): 223–234. https://doi.org/10.1016/j.foreco.2007.01.012

Vazquez, J.A.G. and Givnish, T.J., 1998. Altitudinal gradients in tropical forest composition, structure and diversity in the sierra de Manantlan, Jalisco, Mexico. J. Ecol., 86: 999–1020. https://doi.org/10.1046/j.1365-2745.1998.00325.x

Watt, A.S., 1964. The community and the individual. J. Ecol., 52(Suppl.): 203–211. https://doi.org/10.2307/2440