Phytosociological analysis on tree diversity in Remuna block, Balasore, Odisha, focusing on its biomass, major macronutrients, and carbon stocks

doi:10.21203/rs.3.rs-4512641/v1

Global climate changes, habitat loss, and reduction of biodiversity are significant threats demanding an investigation into the relationship between tree diversity and human well-being to maintain biodiversity and carbon stock. Tree species diversity was studied to comprehend concurrent variation in the phyto-sociological analysis, biomass, carbon stock changes, and five major macronutrient contents in the tropical moist deciduous area of Remuna block, Balasore, Odisha, India. A total of 30 sample plots (20 x 20 metres) were laid that included 422 tree individuals of 39 species belonging to 33 genera and 17 families. The Fabaceae family was the most dominant, with 11 species. The dominant tree species was Shorea robusta with an important value of index (IVI) of 61.48. Some of the dominant species that contributed to above-ground biomass were Shorea robusta, Ficus benghalensis, and Ficus religiosa. Total biomass and carbon stocks were maximum in Shorea robusta and was found to be 6508.32 ton and 3254.16 ton, respectively, and minimum in the species Syzygium cumini with 8.32 ton and 4.16 ton respectively. By using biomass equations and through conversion of nutrient concentrations to nutrient contents, calcium was found to be most abundant, followed by nitrogen, potassium, magnesium, and phosphorus in Shorea robusta. The study will be helpful in understanding changes in the plant community and thereby developing location-specific strategies for conservation of valuable rare plants in the Remuna Block as well as sustainable utilisation of biodiversity in the future.

Botany

Phytosociological

Ecosystem

Biomass

macro nutrient carbon stock

Conservation

Climate change, habitat loss, and biodiversity decline are major threats in the 21st century. Human overgrowth has resulted in the loss of tropical forests, required conservation-oriented management strategies to ensure sustainability (Kumar et al. 2006). Forest land conversion having an impact on nutrient cycling, ecosystem productivity, and species diversity (Srivastava et al. 2020). Tropical forest ecosystems species composition and interaction are not fully understood, with new species added daily and many listed as threats. Species composition, diversity, dominance, distribution pattern, and physiognomy are key attributes of plant communities. Natural or human-induced changes can significantly modify community stratification and functionality (Suchiang et al. 2020). A balanced ecosystem is diverse, interdependent, and sustainable. A Phyto-sociological survey of tree species is crucial for assessing structural and functional stability. Forests are crucial for the terrestrial carbon cycle, containing a significant amount of terrestrial biomass (Bonan 2008). International communities are implementing projects to safeguard biodiversity and carbon reserves in tropical forests, which store over 80% of terrestrial vegetation's CO₂ (Van de Perre et al. 2018). The estimated all over the world forest carbon stock is 861 ± 66 Pg C, with 30% in soil, 42% in biomass, 10% in dead wood, and 5% in litter. (Pan et al. 2011). Land use, deforestation, fragmentation, CO2 emissions, invasive species, resource overexploitation, and climate change are all contributing to the rapidly extinction of tropical forests (Zhou et al. 2006; Tan et al. 2015). Tropical forests are rapidly disappearing due to factors like land use, deforestation, fragmentation, CO2 emissions, invasive species, resource overexploitation, and climate change. Monitoring long-term tree species composition is crucial for assessing climate change response, vegetation dynamics, and conservation needs.

Many workers have been diligently studying the vegetation structure, species composition, and regeneration status of tropical dry deciduous trees in eastern India to investigate the effects of man intrusion and species loss. (Narayan and Anshuali 2015a, Gupta and Misha 2019, Mastan et al. 2020). Quantitative assessments of plant diversity in tropical moist and dry deciduous forests of Odisha have also been conducted. Remuna's tropical climate is characterized by high humidity and hot temperatures. Hence tree species are well established and have been developed in a sustainable manner.1) The study conducted a comprehensive phytosociological analysis of the tree diversity, considering parameters like density, abundance, frequency, and Important Value Index etc., to plan management interventions for sustainable biodiversity development and livelihood support in Remuna Block and 2) To evaluate the changes in biomass, carbon stocks, and five major macro nutrient content in the Remuna block.

2.1. Study site:

Balasore is one of the coastal districts of Odisha. It is located in the northernmost part of the state. The district is located at 21° 3' to 21° 59' north latitude and 86° 20' to 87° 29' east longitude. It is one of the ethnically blessed districts of Odisha. It consists of 12 blocks of which Remuna block is one of the tribal dominated areas of Odisha. Its geographical coordinates are 21.52’99” N and 86.88’35” E. Remuna block covers an area of 130 sq. km, of which 99.54 sq. km are rural areas and 30.47 sq. km are urban areas.

2.2. Data collection:

The research conducted were conducted from July 2019 to February 2020 to cover an entire range of vegetation. The area surveys were conducted using a sampling strategy. Quadrate techniques were used during vegetation surveys. (Misra 1968). The random sample approach was used to acquire data on tree species. A total of 30 sample plots (20 x 20 metres) were placed up in different areas of Remuna Block to investigate ecosystem structure, composition, and above-ground biomass of tree species. These plots had trees with a diameter at breast height (DBH) of at least 1.3 metres (Marimon et al. 2002; Mishra et al. 2013). Trees having buttresses were measure above the buttress root. Species were identified in the field with the help of a standard flora book (The flora of Orissa by H.O. Saxena and M. Brahman 1994) using standard botanical keys. Presented accepted names and family affiliations were assigned to the identified tree species using an online database (The Plant list 2013). Girth was measured by using 10-meter tape. Phytosociological parameters indicated below were analysed by the following methods and formulas (Curtis 1959, Misra 1968): -

Density = \(\frac{Total number of individuals of a species in all quadrates }{Total number of quadrates studied }\)

Relative Density = \(\frac{Density of the species }{Total density of all the species }\) ×100

Frequency (%) = \(\frac{Number of quadrates in which the species occured }{Total number of quadrates studied }\) ×100

Relative Frequency =\(\frac{Frequency of the species }{Total frequency of all species }\)×100

Abundance= \(\frac{Total number of individuals of a species in all quadrates}{Total number of quadrates in which the species occured }\)

Relative Abundance = Relative Frequency + Relative Density

Relative Dominance =\(\frac{Total basal area of a species }{Total basal area for all species }\) ×100

IVI = Relative Density + Relative Frequency + Relative Dominance

Basal area\({(m}^{2}\)) = Area occupied at breast height (1.3m) =\(\pi (DBH/{2)}^{2}\)

2.3 Population Structure:

The GBH method was used to measure the population structure of plant species, focusing on their girth at 1.3 m above ground. The population was grouped according to size classes, using the following DBH classes: 10–31 cm (sapling), 32–66 cm (bole), 67–101 cm (post bole), 102–136 cm (mature tree), 137–171 cm (over mature tree), and > 171 cm (old tree) (Saxena et al. 1984). The number of individuals in each girth class was estimated and the percent density of individuals of each girth class was calculated.

Percent density = \(\frac{Number of individuals in each girth class}{Total number of individuals in all girth classes }\) × 100

2.4 Regeneration potential, biomass and nutrient contents:

The study assessed the regeneration potential of tree species using Shankar's 2001 approach, which involved counting species per Remuna Block and dividing each category by the total, producing a percentage value for each diversity regeneration category.

The calculator calculates the dry mass of a tree's aerial portion and its components (stem wood, foliage, branches, and bark) based on tree diameter and height, adjusting the equations on thousands of samples (Lambert, M.-C.; Ung, C.-H.; Raulier, F. 2005). At the stand scale, equations were developed to calculate biomass and nutrient contents (nitrogen, phosphorus, potassium, calcium, magnesium) for the different tree components (stem wood, foliage, branches and bark) of the most abundant tree species using basal area. Biomass and nutrients can be estimated for a species within a mixed stand. These values can be estimated for generic categories of deciduous or coniferous stands (for a known species that is not on the list or for an unknown species) (Lambert et al. 2005; Ung et al. 2008). When computing nutrient removal, species-level differences are inconsequential for stem-only harvesting but important to consider when branches and foliage are also removed from sites. However, managers have so far lacked the tools needed to move beyond this assertion when making decisions about harvesting intensities. The below-ground biomass (BGB) was calculated by multiplying above-ground biomass, taking 0.26 as the root-to-shoot ratio (Cairns et al. 1997; Ravindranath and Ostwald 2008). The carbon content in biomass was calculated as 50% of the living biomass (Ravindranath et al. 1997).

Globally, terrestrial tree ecosystems give varies biological communities due to their continuously shifting landscape and geoclimatic problems (Herben et al. 2003). The distribution pattern of plant species in an ecosystem reflects its function and biomass type (Enquist 2002; Myklestad & Saetersdal 2004). Understanding the floristic makeup of natural ecosystems and habitat types is essential for sustainable long-term natural resource management (Ewald 2003; Kumar et al. 2019). During this study of tropical forest composition, identified 422 individuals larger than 15 cm DBH, belonging to 39 species, 33 genera, and 17 families in the 30 plots. The highest DBH was measured in the case of Ficus benghalensis (779 cm) followed by Ficus religiosa (761cm), Tamarindus indica (673cm), Azadirachta indica(362cm), Ficus carica (336cm), Tectona grandis (328 cm), Out of 39 species, Shorea robusta was regular, while Pterocarpus marsupium, Tectona grandis and Terminalia tomentosa were randomly distributed.

The tree species that dominated (according to Importance value index) they were Shorea robusta (61.48), Pterocarpus marsupium (16.89), Terminalia tomentosa (16.42), Azadirachta indica (14.95), Tectona grandis (14.37) and lowest in Lagerstroemia parviflora (1.22) (Table 1).Family wise distribution revealed that Fabaceae (11 Species), Combretaceae (5 Species), Moraceae(4 Species) ,Rubiaceae(3 Species), Annonaceae, Meliaceae & Sapotaceae (2 Species each) and others with one species each(Fig. 3).

Table 1

**Phytosociological analysis of tree species in Remuna, Balasore, Odisha.** Note: - NOI- Number of individuals, NPSO- Number of plots in which species occurred, D- Density, RD- Relative density, F- Frequency, RF-Relative frequency, AB- Abundance, RA- Relative Abundance, IVI- Importance value index
SL.NO.	BOTANICAL NAME	Family	Local name	NOI	NPSO	D	RD	F	RF	AB	AB/F	RA	Relative Dominance	IVI
1	Acacia auriculiformis A.Cunn. ex Benth.	Fabaceae	Akashia	15	3	0.50	3.55	10.00	2.44	5.00	0.50	5.99	1.76	7.75
2	Aegle marmelos (L.) Correa	Rutaceae	Bela	5	2	0.17	1.18	6.67	1.63	2.50	0.38	2.81	0.35	3.16
3	Albizia lebbeck (L.) Benth	Fabaceae	Sirisa	12	3	0.40	2.84	10.00	2.44	4.00	0.40	5.28	1.83	7.11
4	Anogeissus latifolia (Roxb.ex.DC.) wall.ex Guill & per	Combretaceae	Dhaura	12	2	0.40	2.84	6.67	1.63	6.00	0.90	4.47	1.50	5.97
5	Azadirachta indica A.juss	Meliaceae	Neem	19	7	0.63	4.50	23.33	5.69	2.71	0.12	10.19	4.76	14.95
6	Butea parviflora Roxb.	Fabaceae	Palasha	7	2	0.23	1.66	6.67	1.63	3.50	0.53	3.28	1.07	4.35
7	Careya arborea Roxb.	Lecythidaceae	Kumbha	12	3	0.40	2.84	10.00	2.44	4.00	0.40	5.28	1.86	7.14
8	Cassia fistula L.	Fabaceae	Sunari	5	1	0.17	1.18	3.33	0.81	5.00	1.50	2.00	0.28	2.28
9	Croton roxburghii Balakr.	Euphorbiaceae	Putuli	2	1	0.07	0.47	3.33	0.81	2.00	0.60	1.29	0.12	1.41
10	Dalbergia sisoo Roxb.	Fabaceae	Sisso	12	4	0.40	2.84	13.33	3.25	3.00	0.23	6.10	2.67	8.77
11	Diospyros melanoxylon Roxb.	Fabaceae	Kendu	6	2	0.20	1.42	6.67	1.63	3.00	0.45	3.05	0.38	3.43
12	Emblica officinalis L.	Phyllanthaceae	Anola	4	2	0.13	0.95	6.67	1.63	2.00	0.30	2.57	0.25	2.82
13	Ficus benghalensis L.	Moraceae	Bara	5	4	0.17	1.18	13.33	3.25	1.25	0.09	4.44	5.86	10.30
14	Ficus carica L.	Moraceae	Dimiri	7	4	0.23	1.66	13.33	3.25	1.75	0.13	4.91	1.61	6.52
15	Ficus elastica Roxb.exHornem	Moraceae	Rabar	5	2	0.17	1.18	6.67	1.63	2.50	0.38	2.81	0.63	3.44
16	Ficus religiosa L.	Moraceae	Aswastha	8	2	0.27	1.90	6.67	1.63	4.00	0.60	3.52	5.86	9.38
17	Haldina cordifolia (Roxb.) Ridsdale	Rubiaceae	Kurma	12	3	0.40	2.84	10.00	2.44	4.00	0.40	5.28	2.87	8.15
18	Lagerstroemia parviflora Roxb.	Lythraceae	Sidha	1	1	0.03	0.24	3.33	0.81	1.00	0.30	1.05	0.17	1.22
19	Madhuca indica J.F. Gmel	Sapotaceae	Mahula	8	3	0.27	1.90	10.00	2.44	2.67	0.27	4.33	1.30	5.63
20	Mangifera indica L.	Anacardiaceae	Amba	10	3	0.33	2.37	10.00	2.44	3.33	0.33	4.81	2.02	6.83
21	Miliusa velutina (Dunal)Hook.f.& Thomas	Annonaceae	Parashi	11	2	0.37	2.61	6.67	1.63	5.50	0.83	4.23	1.32	5.55
22	Millettia pinnata (L.) Panigrahi	Fabaceae	Karanja	4	1	0.13	0.95	3.33	0.81	4.00	1.20	1.76	1.65	3.41
23	Mimusops elengi L.	Sapotaceae	Boula	4	2	0.13	0.95	6.67	1.63	2.00	0.30	2.57	0.36	2.93
24	Mitragyna parvifolic (Roxb.) Korth	Rubiaceae	Godikimia	3	2	0.10	0.71	6.67	1.63	1.50	0.23	2.34	0.89	3.23
25	Neolamarckia cadamba (Roxb.) Bosser	Rubiaceae	kadamba	5	2	0.17	1.18	6.67	1.63	2.50	0.38	2.81	0.30	3.11
26	Polyalthia longifolia Sonn.	Annonaceae	Debadaru	16	4	0.53	3.79	13.33	3.25	4.00	0.30	7.04	0.51	7.55
27	Pterocarpus marsupium Roxburgh	Fabaceae	Piasal	23	6	0.77	5.45	20.00	4.88	3.83	0.19	10.33	6.56	16.89
28	Senegalia Senegal (L.) Britton	Fabaceae	Babul	12	2	0.40	2.84	6.67	1.63	6.00	0.90	4.47	0.83	5.30
29	Shorea robusta Roth	Dipterocarpaceae	Sal	79	17	2.63	18.72	56.67	13.82	4.65	0.08	32.54	28.80	61.34
30	Soymida febrifuga (Roxb.) Juss	Meliaceae	Rohini	4	3	0.13	0.95	10.00	2.44	1.33	0.13	3.39	0.43	3.82
31	Syzygium cumini (L.) Skeels	Myrtaceae	Jamu	3	1	0.10	0.71	3.33	0.81	3.00	0.90	1.52	0.06	1.58
32	Tamarindus indica L.	Fabaceae	kainya	6	3	0.20	1.42	10.00	2.44	2.00	0.20	3.86	3.28	7.14
33	Tectona grandis L.f.	Lamiaceae	Saguan	23	5	0.77	5.45	16.67	4.07	4.60	0.28	9.52	4.85	14.37
34	Terminalia arjuna (Roxb.) Wight & Arn	Combretaceae	Arjuna	14	2	0.47	3.32	6.67	1.63	7.00	1.05	4.94	2.33	7.27
35	Terminalia bellirica (Gaertn.) Roxb.	Combretaceae	Bahada	6	3	0.20	1.42	10.00	2.44	2.00	0.20	3.86	0.76	4.62
36	Terminalia chebula Retz.	Combretaceae	Harida	8	5	0.27	1.90	16.67	4.07	1.60	0.10	5.96	3.19	9.15
37	Terminalia tomentosa Willd.	Combretaceae	Asana	25	6	0.83	5.92	20.00	4.88	4.17	0.21	10.80	5.62	16.42
38	Xylia xylocarpa Roxb. Taub.	Fabaceae	Kongada	3	1	0.10	0.71	3.33	0.81	3.00	0.90	1.52	0.66	2.18
39	Ziziphus mauritiana Lam.	Rhamnaceae	Barakoli	6	2	0.20	1.42	6.67	1.63	3.00	0.45	3.05	0.08	3.13

The distribution of plant regeneration potential girth classes was as follows: A < B < C < D < E > F. The majority of the Percent density was confined in old trees (22.99), mature (28.67) & over mature trees (36.73) (Table 3 and Fig. 4). The study revealed a forest with Climax vegetation, with a higher proportion of mature and over mature trees compared to old trees.

Table 2

Storage of Biomass, Carbon and 5 major macro nutrient contents (Nitrogen, Phosphorus, Potassium, Calcium and Magnesium) of the tree species in Remuna Block, Balasore, Odisha.
SL.NO.	BOTANICAL NAME	Above ground biomass (in ton)	Below ground biomass (in ton)	Carbon storage (in ton)	Nitrogen (in ton)	Phosphorus (in ton)	Potassium (in ton)	Calcium (in ton)	Magnesium (in ton)
1	Acacia auriculiformis	256.1	66.58	161.34	0.54	0.06	0.34	0.77	0.09
2	Aegle marmelos	46.71	12.14	29.42	0.1	0.012	0.063	0.14	0.017
3	Albizia lebbeck	280.61	72.95	176.78	0.59	0.07	0.37	0.84	0.1
4	Anogeissus latifolia	220.55	57.34	138.94	0.46	0.05	0.29	0.66	0.08
5	Azadirachta indica	797.44	207.33	502.38	1.66	0.2	1.06	2.39	0.28
6	Butea parviflora	163.89	42.61	103.25	0.34	0.04	0.21	0.49	0.05
7	Careya arborea	284.92	74.07	179.49	0.6	0.074	0.381	0.859	0.103
8	Cassia fistula	36.54	9.5	23.02	0.07	0.009	0.049	0.112	0.013
9	Croton roxburghii	16.21	4.21	10.21	0.03	0.004	0.022	0.049	0.005
10	Dalbergia sisoo	437.21	113.67	275.44	0.91	0.114	0.583	1.313	0.15
11	Diospyros melanoxylon	49.74	12.93	31.33	0.1	0.013	0.067	0.152	0.018
12	Emblica officinalis	32.97	8.57	20.77	0.071	0.008	0.044	0.1	0.012
13	Ficus benghalensis	1308.72	340.26	824.49	2.68	0.34	1.72	3.86	0.47
14	Ficus carica	266.64	69.32	167.98	0.55	0.06	0.35	0.8	0.09
15	Ficus elastica	93.69	24.35	59.02	0.19	0.02	0.12	0.28	0.03
16	Ficus religiosa	1198.94	311.72	755.33	2.46	0.31	1.58	3.55	0.43
17	Haldina cordifolia	476.74	123.95	300.345	0.996	0.124	0.635	1.43	0.17
18	Lagerstroemia parviflora	27.07	7.03	17.05	0.056	0.007	0.036	0.081	0.009
19	Madhuca indica	201.89	52.49	127.19	0.425	0.53	0.27	0.608	0.073
20	Mangifera indica	325.97	84.75	205.36	0.68	0.085	0.43	0.98	0.11
21	Miliusa velutina	194.24	50.5	122.37	0.411	0.051	0.26	0.588	0.07
22	Millettia pinnata	255.49	66.42	160.955	0.53	0.06	0.34	0.77	0.09
23	Mimusops elengi	85.68	22.27	53.975	0.18	0.022	0.11	0.25	0.031
24	Mitragyna parvifoli	54.97	14.29	34.63	0.305	0.038	0.195	0.438	0.053
25	Neolamarckia cadamba	39.3	10.21	24.755	0.08	0.01	0.05	0.12	0.014
26	Polyalthia longifolia	58.01	15.08	36.545	0.12	0.015	0.079	0.179	0.049
27	Pterocarpus marsupium	1125.05	292.51	708.78	2.34	0.29	1.49	3.36	0.4
28	Senegalia Senegal	110.337	28.68	69.51	0.23	0.02	0.14	0.33	0.04
29	Shorea robusta	5165.34	1342.98	3254.16	10.72	1.35	6.86	15.41	1.87
30	Soymida febrifuga	70.53	18.33	44.43	0.147	0.018	0.094	0.211	0.025
31	Syzygium cumini	6.61	1.71	4.16	0.014	0.001	0.009	0.02	0.002
32	Tamarindus indica	636.31	165.44	400.875	1.31	0.16	0.84	1.89	0.23
33	Tectona grandis	786.83	204.57	495.7	1.64	0.2	1.05	2.36	0.28
34	Terminalia arjuna	361.6	94.01	227.805	0.76	0.09	0.48	1.09	0.13
35	Terminalia bellirica	112.6	29.27	70.935	0.23	0.02	0.15	0.34	0.04
36	Terminalia chebula	581.85	151.28	366.565	1.2	0.15	0.77	1.73	0.21
37	Terminalia tomentosa	921.72	239.64	580.68	1.92	0.24	1.22	2.76	0.33
38	Xylia xylocarpa	107.9	28.05	67.975	0.022	0.028	0.144	0.324	0.039
39	Ziziphus mauritiana	8.57	2.22	5.395	0.019	0.002	0.012	0.027	0.003

Table 3

Population Structure and Regeneration Potential of the tree species in Remuna Block, Balasore.
SL.NO.	GIRTH CLASS	RANGE OF CENTIMETER	DBH CATEGORY	NUMBER OF PLANTS	PERCENT DENSITY
1	A	10–31 cm	Sapling	1	0.24
2	B	32–66 cm	Bole	3	0.71
3	C	67–101 cm	Post bole	45	10.66
4	D	102–136 cm	Mature	121	28.67
5	E	137–171 cm	Over mature	155	36.73
6	F	> 171 cm	Old trees	97	22.99

Among tree species, the top 5 that contribute the most above ground biomass are Shorea robusta (5165.34 ton), Ficus benghalensis (1308.72 ton), Ficus religiosa (1198.94 ton), Pterocarpus marsupium (1125.05 ton), Terminalia tomentosea (921.72 ton) respectively and lowest in the species Syzygium cumini ( 6.61 ton) ( Table 2) .Among tree species, the top 5 that having most Carbon stock is Shorea robusta (3254.16 ton), Ficus benghalensis (824.49 ton), Ficus religiosa (755.33 ton), Pterocarpus marsupium (708.78ton),Terminalia tomentosa (580.68 ton) and lowest carbon stock in the species Syzygium cumini (4.16 ton) ( Table 2) .The maximum macro nutrients were found in Stem wood, Foliage,Branch, Bark of the species of Shorea robusta, where Nitrogen was 10.72 ton, Phosphorus was 1.35 ton, Potassium was 6.86 ton, Calcium was 15.41 ton and Magnesium was 1.87 ton. In lowest nutreient content in the species Syzygium cumini (Table 2). In every tree species of Remuna, out of 5 macro nutrients, Calcium content was found in maximum amount in comparison to others. Because of laterites and alluvial soil, which formation belonging to Archaean system that include laterite stone, basic granulite, intermediate to acid charnockite veins and Khondolites which are the oldest.

However, some tree products which they use for their business purpose are Azadirachta indica, Millettia pinnata & Shorea robusta for oil production, Diospyros melanoxylon for leaf, Aegle marmelos, Mangifera indica, Syzygium cumini, Tamarindus indica, Ziziphus mauritiana, Emblica officinalis, Madhuca indica, Terminalia bellirica & Terminalia chebula for medicinal purpose. The declining abundance of medicinal plant resources is mostly caused by unsustainable harvesting, a lack of awareness, and villagers' unrestricted grazing, resulting in to a decline in traditional indigenous knowledge.

The study provides valuable data on tree species in Remuna Block, emphasising the essential role of management in sustaining carbon stocks in the natural environment. The study reveals that older trees have More biomass and carbon stock per unit. Many tree species with low IVI and other parameters requires more attention. Special care should be given to There are juvenile tree species in these locations. The forest has a strong regeneration state, providing opportunity to study forest dynamics and potential changes in species relative abundance. The protected study area is facing destruction due to frequent village visits and livestock overgrazing, leading to forest fragmentation and damage to biodiversity, despite its protected status. The study in Remuna suggests that educating locals and implementing rules can help reduce natural forest depletion. A subsequent census will assist in the restoration and management of the region for longer-term conservation planning.

All authors have read, understood, and have complied as applicable with the statement on “Ethical responsibilities of Authors” as found in the Instructions for Authors”.

Ethics approval and consent to participate

The submitted work should be original and should not have been published elsewhere in any form or language (partially or in full), unless the new work concerns an expansion of previous work.

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Competing Interests

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper

Author contributions

Baishnab Charan Muduli: Writing – original draft, Methodology, Investigation, Formal analysis, Field visit, Data collection, Software, Resources Data curation, Conceptualization. Netajee Tapas Kumar Sahoo: Writing – original draft, Methodology, Investigation, Formal analysis, Field visit, Data collection, Resources Data curation. Subhadarshani Dhall: Writing – review, Resources, Methodology, Investigation, Formal analysis, Data curation.

Funding

NA

Availability of data and materials

Data will be made available on request.

Acknowledgement

Thanks to Remuna peoples help, Support at the times of filed study.

Kumar A, Marcot BG, Saxena A (2006) Tree species diversity and distribution patterns in tropical forests of Garo Hills. Current science 1370-81.
Bonan GB (2008) Forests and climate change: forcings, feedbacks, and the climate benefits of forests. Science 320(5882):1444-9.
Cairns MA, Brown S, Helmer EH, Baumgardner GA (1997) Root biomass allocation in the world's upland forests. Oecologia 111:1-1.
Curtis JT (1959) The vegetation of Wisconsin: an ordination of plant communities. University of Wisconsin Pres.
Enquist BJ (2002) Universal scaling in tree and vascular plant allometry: toward a general quantitative theory linking plant form and function from cells to ecosystems. Tree physiology 22(15-16):1045-64.
Ewald J (2003) A critique for phytosociology. Journal of vegetation science 14(2),291-296.
Gupta B, Mishra TK (2019) Analysis of tree diversity and factors affecting natural regeneration in fragmented dry deciduous forests of lateritic West Bengal. Tropical Ecology
Herben T, Krahulec F, Hadincová V, Pecháčková S, Wildová R (2003) Year-to-year variation in plant competition in a mountain grassland. Journal of Ecology 103-13.
Kumar D, Scheiter S (2019) Biome diversity in South Asia-How can we improve vegetation models to understand global change impact at regional level? Science of the Total Environment 671:1001-16.
Lambert MC, Ung CH, Raulier F (2005) Canadian national tree aboveground biomass equations. Canadian Journal of Forest Research 35(8):1996-2018.
Marimon BS, Felfili JM, Lima ES (2002) Floristics and phytosociology of the gallery forest of the Bacaba Stream, Nova Xavantina, Mato Grosso, Brazil. Edinburgh Journal of Botany 59(2):303-18.
Mastan T, Ankalaiah C, Ramana CV, Reddy MS (2020) Assessment of tree diversity in nithyapoojakona dry deciduous forest of Sri Lankamalleswara wildlife sanctuary, southern eastern ghats, India. Indian Journal of Ecology 47(2):390-6.
Mishra AK, Singh J, Kumar V, Srivastava R, Srivastava S (2013) Standing carbon stock estimation in different tree species grown in dry tropical forests of vindhyan highland, Mirzapur, India.
Misra R. Ecology work book’ (N. Delhi) (1998) New Delhi, India: Oxford and IBH Publ. House.
Myklestad Å, Sætersdal M (2004) The importance of traditional meadow management techniques for conservation of vascular plant species richness in Norway. Biological conservation 118(2):133-9.
Narayan CA, Anshumali J (2015) Diversity indices and importance values of a tropical deciduous forest of Chhotanagpur plateau, India. J Biodiv Environ Sci 7:358-67.
Pan Y, Birdsey RA, Fang J, Houghton R, Kauppi PE, Kurz WA, Phillips OL, Shvidenko A, Lewis SL, Canadell JG, Ciais P (2011) A large and persistent carbon sink in the world’s forests. Science 19;333(6045):988-93.
Ravindranath NH, Ostwald M (2008) Methods for estimating above-ground biomass. Carbon inventory methods handbook for greenhouse gas inventory, carbon mitigation and roundwood production projects 113-47.
Ravindranath NH, Somashekhar BS, Gadgil M (1997) Carbon flow in Indian forests. Climatic change. 35:297-320.
Saxena HO and Brahmam M 1994-1996., Vol. 1–4. Flora of Odisha Odisha Forest evelopment Corporation Ltd. and Regional D Research Laboratory, Bhubaneswar, 2918
Saxena AK, Singh JS (1984) Tree population structure of certain Himalayan Forest associations and implications concerning their future composition. Vegetatio.58(2):61-9.
Shankar U (2001) A case of high tree diversity in a sal (Shorea robusta)-dominated lowland forest of Eastern Himalaya: Floristic composition, regeneration and conservation. Current Science. 776-86.
Srivastava R, Mohapatra M, Latare A (2020) Impact of land use changes on soil quality and species diversity in the Vindhyan dry tropical region of India. Journal of Tropical Ecology. 36(2):72-9.
Suchiang BR, Nonghuloo IM, Kharbhih S, Singh PP, Tiwary R, Adhikari D, Upadhaya K, Ramanujam P, Barik SK (2020) Tree diversity and community composition in sacred forests are superior than the other community forests in a human-dominated landscape of Meghalaya. Tropical Ecology 61:84-105.
Tan Z, Liu S, Sohl TL, Wu Y, Young CJ (2015) Ecosystem carbon stocks and sequestration potential of federal lands across the conterminous United States. Proceedings of the National Academy of Sciences 112(41):12723-8.
Ung CH, Bernier P, Guo XJ (2008) Canadian national biomass equations: new parameter estimates that include British Columbia data. Canadian Journal of Forest Research 38(5):1123-32.
Van de Perre F, Willig MR, Presley SJ, Bapeamoni Andemwana F, Beeckman H, Boeckx P, Cooleman S, de Haan M, De Kesel A, Dessein S, Grootaert P (2018) Reconciling biodiversity and carbon stock conservation in an Afrotropical Forest landscape. Science advances 4(3): eaar6603.
Zhou G, Liu S, Li Z, Zhang D, Tang X, Zhou C, Yan J, Mo J (2006) Old-growth forests can accumulate carbon in soils. Science 314(5804):1417.

The authors declare no competing interests.

Phytosociological analysis on tree diversity in Remuna block, Balasore, Odisha, focusing on its biomass, major macronutrients, and carbon stocks

Status:

Version 1

Abstract

Figures

1. Introduction

2. Material and Methodology

2.1. Study site:

2.2. Data collection:

2.3 Population Structure:

2.4 Regeneration potential, biomass and nutrient contents:

3. Result and discussion

4. Conclusion

Declarations

References

Additional Declarations

Status:

Version 1