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Article

Plant Community Composition and Carbon Stocks of a Community Reserve Forest in North-East India

by
Aosanen Ao
1,
Sapu Changkija
2,
Francis Q. Brearley
3,* and
Shri Kant Tripathi
1
1
Department of Forestry, Mizoram University, Aizawl 796004, Mizoram, India
2
Department of Genetics and Plant Breeding, Nagaland University, Medziphema 797106, Nagaland, India
3
Department of Natural Sciences, Manchester Metropolitan University, Manchester M1 5GD, UK
*
Author to whom correspondence should be addressed.
Forests 2023, 14(2), 245; https://doi.org/10.3390/f14020245
Submission received: 11 December 2022 / Revised: 12 January 2023 / Accepted: 18 January 2023 / Published: 28 January 2023
(This article belongs to the Section Forest Biodiversity)
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Abstract

:
Anthropogenic activities are altering the structure and functioning of forests and their services to society. However, we know little about the degree to which such activities are changing the health of forests through edge effects in fragmented forests in different regions of the world. The present study was carried out in Minkong Community Reserve Forest of Nagaland (North-east India) with the aim to determine the effects of anthropogenic activities on floristic composition and diversity, population structure, and biomass and carbon (C) stocks in the core zone (CZ) and buffer zone (BZ) of the forest. We established 15 plots of 0.04 ha each in the two forest zones. We identified 31 trees, 18 shrubs, and 22 herbs in the CZ, and 22 trees, 25 shrubs, and 24 herbs in the BZ; tree species diversity was greater in the CZ whereas the diversity of shrubs and herbs was greater in the BZ. The values for tree density and basal area in the CZ and BZ were 303 and 197 individuals ha−1 and 32.6 and 22.2 m2 ha−1, respectively; in contrast, the shrub and herb density increased in the BZ (4470 and 50,200 individuals ha−1) compared to that of the CZ (2530 and 35,500 individuals ha−1). The total stand biomass (including that below-ground) was 327 Mg ha−1 in the CZ and 224 Mg ha−1 in the BZ. Similarly, the total ecosystem C stocks in the CZ and BZ were 224 Mg C ha−1 and 173 Mg C ha−1, indicating that the overall ecosystem C pool including soil in the CZ was approximately 30% greater than the BZ. These results show how fragmentation and anthropogenic disturbance can reduce forest diversity and C stocks and that community forest management can play a role in conserving biodiversity and act as an ecosystem management tool to mitigate climate change.

1. Introduction

Globally, forests play vital roles in conserving biodiversity, biogeochemical cycling including storing a large amount of carbon (C) in the vegetation and soil, and sustaining peoples’ livelihoods [1]. Tropical forests contribute significantly to the global terrestrial C stocks and harbour half of the world’s biodiversity whilst supporting human populations by providing a wide range of goods and services. However, these forests are regularly over-exploited leading to the loss of forest cover (>10 million ha year−1), thereby losing their potential for ecological service provision [2,3]. Tropical forests, with appropriate management, can provide economic benefits through ecotourism, non-wood forest products, a sustainable timber source, and also through emerging C financing mechanisms [4,5]. Tropical moist forests are characterized by the high density of understory trees, high species diversity, and a high degree of endemism [6]. Habitat fragmentation due to anthropogenic activities (e.g., agriculture, road construction, urbanization, etc.) has become one of the most pervasive and conspicuous forms of disturbance in tropical rain forests [7,8,9]. Studies on tropical forest fragmentation have shown edge effects to influence changes in the abiotic environment impacting upon forest structure and composition. Studies on a range of tropical forests reported the influence of fragmentation on ecosystem processes resulting in increasing biomass loss, tree mortality rates, and ultimately changes to the population structure of the forest [10,11,12,13].
Community forestry plays an important role in forest conservation, where the local people are involved in the management and protection of the forest [14,15]. Community forestry is practiced over the world but it is mainly dominant in Asia and has had a long history in India [16]. The Indian state of Nagaland, geographically located in the north-east of the country within the Himalaya and Indo-Burma biodiversity hotspots, is endowed with diverse vegetation cover that supports the predominantly tribal communities in their livelihoods. The constitution of India has provided special customary rights to the population of the state for the traditional use of natural resources, and thus over 85% of the natural habitats are owned by individuals or clans through the co-ordination of village councils and other traditional institutions [17]. Since most of the economic activities in rural areas are dependent on natural resources, the over-exploitation of forest resources in recent years is posing a threat to the region’s biodiversity.
Minkong Community Reserve Forest is managed by local communities within a mountainous region of Mokokchung district in the state of Nagaland surrounded by three villages, namely, Chuchuyimpang, Longmisa, and Sungratsu. The forest, which is owned by the local communities, is traditionally managed by laying down certain customary laws such as restricting the cutting of trees, gathering of natural resources, or hunting of wild animals from the forest without permission from the local village councils. Heavy fines are levied upon the defaulters to act as a deterrent and help protect the forest.
In this study, we look at the floristic and structural attributes of a community-conserved sub-tropical humid forest and we hypothesize that human disturbance reduces species diversity and C stocks. We also examine the role of edge effects through not only biophysical disturbances but also increased human interference on the forest composition. Therefore, the present study aims to: (i) assess the vegetation community composition (trees, shrubs, and herbs), diversity, and species distribution patterns; (ii) estimate tree biomass and ecosystem C stocks; and (iii) determine how these differ between the core zone and buffer zone of the Minkong Community Reserve Forest of Nagaland in North-east India.

2. Materials and Methods

2.1. Study Area

The study was located in Minkong Community Reserve Forest, having a total area of 2.75 km2 located at 26°21′ N and 94°33′ E and about 1400 m above mean sea level in Mokokchung district, Nagaland, North-east India (Figure 1). The vegetation is sub-tropical evergreen forest [18]. The forest area, which was initially owned by the state government until the 1980s, was handed over to the surrounding village communities which later declared it a Community Reserve Forest with the aim to conserve and protect the biodiversity inhabiting it due to the high level of anthropogenic disturbance at that time. About 40% of the forest area is considered secondary/fallow forests from shifting cultivation practices by the Naga agriculturalists. While the core zone (CZ) is situated in the centre of the reserve forest without any disturbance, the buffer zone (BZ) surrounds this zone and is located about 2 km from the human settlements. The forest soil has, on average, a pH of 5.8 [19] and 3.4% soil organic carbon (SOC) [20].

2.2. Vegetation Sampling

For a detailed quantitative analysis of vegetation, the forest was divided into two zones—the core zone (CZ) in the centre of the reserve forest without disturbance and the buffer zone (BZ) present towards the periphery. Tracts of the forest were selected in each zone for the measurement of species diversity and C stocks. In each zone, 15 quadrats each measuring 20 m × 20 m (0.04 ha) were laid randomly for tree species (DBH ≥ 10 cm). Within each 20 m × 20 m plot were nested two 5 m × 5 m subplots for shrubs and four 1 m × 1 m subplots for herbs (including epiphytes, lithophytes, and climbers). The plant species were photographed and identified, and herbarium vouchers were prepared following Jain and Rao [21]. Vouchers were deposited in the Herbarium, School of Agricultural Sciences and Rural Development, Nagaland University, Medziphema, Nagaland, India. Plant community attributes such as frequency, density, and basal area were analyzed. The importance value index (IVI) of each individual species was calculated to study the dominance of the species. Tree species were classified into different diameter classes to study the population structure of the forest. The Shannon–Weiner diversity index [22] of each lifeform in each quadrat and Sørensen’s similarity index [23] between the CZ and BZ for each of the lifeforms were also calculated. Comparisons between the two zones were made with t-tests using Minitab 19.2, whilst a detrended correspondence analysis ordination was conducted on the three groups of lifeforms (i.e., trees, shrubs, and herbs) using Canoco 5.15 [24].

2.3. Soil Sampling and Analysis

Soil samples were collected from two random locations from each 0.1 ha sampling plot at two depths (0 to 25 cm and 25 to 50 cm). Soil samples collected from five sampling plots were composited to represent one sample with a total of three samples from 15 sampling plots of 0.04 ha from each of the two zones. Soil bulk density was determined using a stainless-steel tube of known inner volume within which soils were oven-dried at 40 °C to constant weight and then passed through a sieve of 2 mm. Soil organic carbon (SOC) was analyzed using the method of Walkley and Black [25].

2.4. Estimation of Plant Biomass and Carbon Stock

Total above-ground biomass of trees (AGBest) was estimated using the allometric equation developed from trees in North-east India by Nath et al. [26]:
AGBest = 0.32 (D2 × Hδ) 0.75 × 1.34
where D is the DBH, H denotes the height of the tree, and δ is wood-specific gravity obtained from the ICRAF database [27].
Below-ground biomass was estimated using the allometric equation developed by Cairns et al. [28]:
BGBest = exp [−1.085 + 0.9256 × ln (AGB)]
The vegetation C stock was estimated assuming 45.6% C content of dry biomass [29]. Total above-ground biomass of shrubs was estimated using equation developed by Ali et al. [30]:
AGB = exp (–3.5 + 1.65 × ln (CD) + 0.842 × ln (H)
where CD is the collar diameter and H denotes the height of the shrub.
The forest floor mass was collected by laying a quadrat of 50 cm × 50 cm in each sampling plot of 0.04 ha. Litter was collected twice in a year (dry and wet seasons) and the mean litter mass of the two seasons was presented. Herb biomass was estimated using the harvest plot method on the basis of fresh/dry weight. All the above- and below-ground vegetation was harvested inside the herb plot after which roots were separated from the shoots and the fresh weight was recorded in the field. About 100 g of a fresh sample of roots and shoots of the herbs was then oven-dried (60 °C) to constant weight. Soil organic carbon (SOC) stock (0 to 50 cm) was estimated as the product of the SOC content, bulk density, and soil depth.
SOC stock (Mg C ha−1) = SOC × BD × SD × 100
where SOC is soil organic carbon content (%), BD is bulk density (g cm3), and SD is soil depth in metres (m). The total ecosystem C stock was calculated by summing total vegetation C stock and SOC stock.

3. Results

The present study showed that species composition varied significantly between the CZ and BZ with the DCA ordinations showing a clear separation of the plots (Figure 2). The total number of tree species recorded in the CZ was 31, which was reduced to 22 species in the BZ. However, the total species richness of shrub and herb species was greater (25 and 24 species) in the BZ and lower (18 and 22 species) in the CZ (Table 1). The dominant families of trees, shrubs, and herbs were: Lauraceae and Moraceae, Rosaceae and Urticaceae, and Leguminosae and Zingiberaceae, respectively. Structural attributes also varied between the two zones. The tree density and basal area were greater (303 individuals ha−1 and 32.6 m2 ha−1) in the CZ which declined to 197 individuals−1 ha−1 and 22.2 m2 ha−1 in the BZ. However, the density of shrub and herb species increased (4470 and 50,200 individuals−1 ha−1) in the BZ compared to the CZ (2530 and 35,500 individuals−1 ha−1) (Table 1).
The Shannon’s diversity index (H’) for tree species was greater (2.11) in the CZ and lower (0.72) in the BZ, whereas the H’ for shrub and herb species showed the opposite pattern (Table 1). Based on IVI values, the most important tree species in the CZ were Betula alnoides (15.4), Choerospondias axillaris (15.3), Garcinia pedunculata (15.3), and Lithocarpus pachyphyllus (15.0). On the other hand, the most important tree species in the BZ were: Lithocarpus elegans (31.6), Morus macroura var. macroura (22.4), and Castanopsis indica (20.5) (Table 2). The most important shrub species in the CZ were Clerodendrum glandulosum (21.7), Eriosolena involucrata (16.9), Millettia pachycarpa (15.7), and Boehmeria japonica (15.5); in contrast, Osbeckia nepalensis (13.7), Dendrocnide sinuata (11.3), and Rubus lucens (11.3) were the most important species in the BZ (Table 2). Moreover, the most important herb species in the CZ were Girardinia diversifolia (22.3), Smilax aspera (17.6), and Commelina benghalensis (16.1); in the BZ, Commelina benghalensis (12.6) was the most important species, along with Curculigo orchioides (12.6) Hellenia speciosa (12.4), and Gomphostemma strobilinum (12.1) (Table 2). The dominance–diversity curves followed a log-normal distribution pattern which indicates that different plant life forms (trees, shrubs, and herbs) showed high equitability and low dominance of species in both zones (Figure 3). The greatest similarity (Sørenson) (73%) between the CZ and BZ was recorded for the herb community, followed by shrubs (46%) and trees (26%); the overall community had 47% similarity between the two zones.
While tree density and basal area were lower in the BZ as compared to the CZ (Table 1), the tree density and basal area showed the greatest occurrences in the 10 to 20 cm DBH range in both zones (Figure 4) with the number of individuals declining with increasing DBH in both zones; there were proportionally fewer trees in the 20 to 30 DBH class in the BZ compared to the CZ. The overall plant biomass and C stock were greater in the CZ than in the BZ. Out of the total biomass (327 Mg ha−1) in the CZ, the tree biomass contributed 98% and the remaining was contributed by shrub, herb, and floor mass. Similarly, of the total biomass (224 Mg ha−1) in the BZ, trees contributed 97%. The overall distribution of tree biomass among different girth classes showed the greatest biomass in the trees of 10 to 30 cm DBH which contributed 79% in the CZ and 71% in the BZ. The maximum tree biomass of 50% and 58% was contributed by the 10 to 20 cm diameter class in the CZ and BZ, respectively (Figure 5).
The total C contributed by different tree species to AGB C varied between the species and was directly associated with the tree basal area. In the CZ, the contribution of major tree species (i.e., Betula alnoides, Bischofia javanica, Cephalotaxus grifithii, Lithocarpus elegans, Quercus lamellosa, Terminalia myriocarpa, and Toona ciliata) was around 40% of the total AGB and C stocks, with a similar contribution of major tree species (i.e., Castanopsis indica, Ilex dipyrena, Lithocarpus elegans, Prunus nepaulensis, Quercus serrata, and Xerospermum noronhianum) in the BZ. The total tree biomass (AGB + BGB) was estimated at 322 Mg ha−1 and 218 Mg ha−1 in the CZ and BZ, respectively (Table 3). The total understory biomass (shrubs + herbs) was 1.90 and 2.94 Mg ha−1 in the CZ and BZ.
The total SOC stock (0 to 50 cm) was not different between the CZ (75 ± 4.51 Mg C ha−1) and the BZ (71 ± 3.45 Mg C ha−1) (Table 4). The total C stored in all ecosystem compartments, including SOC, showed a sum of 224 Mg C ha−1 in CZ and 173 Mg C ha−1 in BZ.

4. Discussion

Community reserve forests can play an important role in biodiversity conservation and provide socio-ecological benefits for regional populations [14,15,31,32,33]; however, overexploitation of these forests, combined with ecological edge effects, can considerably affect their structure and function. In the present study, the CZ and BZ of a community reserve forest in North-east India were studied with respect to their species composition, diversity, biomass, and C stocks. The greater tree species richness in the CZ compared to the BZ may be because of the protection provided by the traditional communities [33] and less exploitation, whereas the lower density and species richness of trees in the BZ, being more closely located to human settlements, is likely due to anthropogenic pressures (e.g., extraction of timber and natural resources, forest fire, and agriculture expansion) along with further environmental changes brought about by the opening of the canopy. The diversity indices in the present study showed the changing pattern of the diversity of various lifeforms in the forest community. The tree community was more diverse than the shrub and herb communities, although this could be due to the greater area sampled for trees. High values of the Shannon–Wiener diversity index (H’) and low dominance are characteristic features of an old-growth forest [34] which was also supported by our study. Additionally, changes in species composition have been shown at the edges of forest fragments with a move towards more early successional species and a decline in the abundance of old-growth specialists [35]. In the BZ, we found, for example, that Macaranga denticulata, a typical secondary forest tree species, was an abundant tree but it was not present in the CZ. In contrast, a greater diversity and density of undergrowth plants (shrubs and herbs) in the BZ may be attributed to a more open canopy due to anthropogenic and natural disturbances allowing more sunlight to reach the forest floor and thus creating favorable microsite conditions enhancing the growth of understory vegetation [36]. The composition of the shrub community in the BZ was clearly distinct from that in the CZ, whereas there was more overlap in the herb community. Similar observations have been reported from other natural undisturbed forests in India [37,38,39,40]. This is supported by the similarity measures (Sørenson) which are the most instinctive and common methods for comparing two or more sites with respect to their species overlap [41]. The low similarity between the CZ and BZ may also be because of succession brought about by disturbance, leading to contrasting micro-environmental conditions [42,43]. Different plant life forms (trees, shrubs, and herbs) recorded from the CZ and BZ showed similar characteristics of dominance–diversity curves with high equitability and low dominance of species. The log-normal distribution pattern in both sites indicates high species richness and equitable distribution of natural resources among the species in the forest ecosystem [44,45]. The reduced proportion of trees in the 20 to 30 cm DBH category in the BZ suggests that this size category is preferentially used by the local communities. In other studies of disturbed forest, larger trees are found at lower proportions leading to changes in the slope of a scaling relationship between stem diameter and density [46,47]. Our results present an interesting comparison to this as large trees seem to be retained in the BZ with medium-sized trees appearing to be preferentially removed.
The estimated above-ground biomass for trees in both zones ranged from 177 to 263 Mg ha−1 with a mean of 220 Mg ha−1 which falls well within the reported range (133 to 262 Mg ha−1) for various natural forests of North-east India [48,49,50,51,52,53,54,55]. Decreased biomass in the BZ may be attributed to lower tree density and size due to various anthropogenic disturbances associated with edge effects [56]. Tree species composition also affects the total biomass and C stock of forests [51,57,58] and the change in species composition in the BZ plots will influence total forest biomass if lighter-wooded species become more dominant. Below-ground biomass contributed about 20% to the total biomass stock in both zones and plays an important role in below-ground C storage; this value is an estimate based on above-ground biomass so it would be valuable to directly measure root biomass in these forests for a more accurate estimate, e.g., [59,60]. Furthermore, in both the zones, tree biomass distribution across diameter classes showed the greatest biomass allocation in smallest classes (10 to 20 cm DBH) which may be due to the occurrence of greater tree density and basal area of the young trees and the lack of particularly large trees due to the montane elevation. A similar study was also conducted in a sacred natural forest of Manipur, North-east India which reported the greatest biomass in the smaller girth class of 30 to 60 cm (equivalent to 10–20 cm DBH) [55]. The greatest familial contribution to total biomass C stocks in both the CZ and BZ was by the Fagaceae, followed by Betulaceae, Sapindaceae, Moraceae, Euphorbiaceae, and Meliaceae, which contributed about 70% of the total biomass among the six families.
There was no difference in the SOC stock between the BZ (71 Mg C ha−1) compared to the CZ (75 Mg C ha−1). It is known that forest conversion to other land-uses such as shifting cultivation or plantations can have a clear effect on SOC stocks with reductions regularly seen [61,62]. It appears that, currently, the low-intensity disturbance in the buffer zone was not severe enough to influence SOC stocks. However, changes in litter input and soil disturbance in the future may influence soil changes, so additional monitoring would be valuable. Determining long-term C sequestration rates and how they may be influenced by disturbance, tree growth, and mortality rates combined with litterfall and other measures of primary production, e.g., [13,59], would be an important next step.

5. Conclusions

We show here that whilst community reserve forests can be valuable for conserving tropical biodiversity, edge effects brought about by human usage of the forest lead to reductions in tree species richness but an increase in shrub and, particularly, herb species richness with a clear impact on the community composition of all three groups of plant life-forms with edge-affected (buffer-zone) plots having a distinct composition to those in the core zone. Total biomass and C stock were both high as compared to other Indian natural forests indicating the high potential of the site to store C in the plant biomass and soil, and the buffer zone can provide similar ecosystem services to that of the core zone if adequate protection is provided. However, the buffer zone can act as an ex situ conservation ground for the valuable local plant species and protect the ecosystem services at a regional level by buffering the human disturbances. We recommend the extension of the buffer zone or the creation of a peripheral zone around Minkong Community Reserve Forest, perhaps in the form of a plantation forest or agroforest, that may help in conserving local species and ecosystem services on a sustained basis. Such an effort may provide livelihood opportunities to the local tribal communities by conserving regional diversity and mitigating climate change.

Author Contributions

Conceptualization, A.A. and S.K.T.; Data curation, A.A.; Formal analysis, A.A., F.Q.B. and S.K.T.; Methodology, A.A. and S.K.T.; Resources, A.A., S.K.T. and S.C.; Writing—draft, A.A., F.Q.B. and S.K.T.; Supervision, S.K.T., S.C. and F.Q.B.; Validation, A.A., S.K.T. and S.C.; Writing—review & editing, A.A., F.Q.B. and S.K.T. All authors have read and agreed to the published version of the manuscript.

Funding

This research was partly supported by a fellowship to A.A. from the Ministry of Tribal Affairs, Government of India (202021-NFST-NAG-00620).

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

Data on species composition is available from the corresponding author.

Acknowledgments

The authors would like to thank the Nagaland Forest Department and the villagers living near the Minkong Community Reserve Forest for granting us permission to collect the data and study the forest vegetation. Our sincere thanks to local residents for extending help as local guides during the field survey.

Conflicts of Interest

This article has no conflict of interest to any person or organization.

References

  1. Pan, Y.; Birdsey, R.A.; Phillips, O.L.; Jackson, R.B. The structure, distribution, and biomass of the world’s forests. Annu. Rev. Ecol. Evol. Syst. 2013, 44, 593–622. [Google Scholar] [CrossRef] [Green Version]
  2. Chazdon, R.L. Second Growth: The Promise of Tropical Forest Regeneration in an Age of Deforestation; University of Chicago Press: Chicago, IL, USA, 2014. [Google Scholar]
  3. FAO; UNEP. The State of the World’s Forests 2020: Forests, Biodiversity and People; FAO: Rome, Italy, 2020. [Google Scholar] [CrossRef]
  4. Lewis, S.L.; Edwards, D.P.; Galbraith, D. Increasing human dominance of tropical forests. Science 2015, 349, 827–832. [Google Scholar] [CrossRef] [PubMed]
  5. Tripathi, S.K. The need for establishing long-term ecological research stations network in India. Curr. Sci. 2010, 98, 21–22. [Google Scholar]
  6. Slik, J.W.F.; Paoli, G.; McGuire, K.; Amaral, I.; Barroso, J.; Bastian, M.; Blanc, L.; Bongers, F.; Boundja, P.; Clark, C. Large trees drive forest aboveground biomass variation in moist lowland forests across the tropics. Glob. Ecol. Biogeogr. 2013, 22, 1261–1271. [Google Scholar] [CrossRef]
  7. Laurance, W.F.; Peres, C.A. Emerging Threats to Tropical Forests; The University of Chicago Press: Chicago, IL, USA, 2006. [Google Scholar]
  8. Taubert, F.; Fischer, R.; Groeneveld, J.; Lehmann, S.; Müller, M.S.; Rödig, E.; Wiegand, T.; Huth, A. Global patterns of tropical forest fragmentation. Nature 2018, 554, 519–522. [Google Scholar] [CrossRef]
  9. Haddad, N.M.; Brudvig, L.A.; Clobert, J.; Davies, K.F.; Gonzalez, A.; Holt, R.D.; Lovejoy, T.E.; Sexton, J.O.; Austin, M.P.; Collins, C.D.; et al. Habitat fragmentation and its lasting impact on Earth’s ecosystems. Sci. Adv. 2015, 1, e1500052. [Google Scholar] [CrossRef] [Green Version]
  10. Harper, K.A.; McDonald, S.E.; Burton, P.J.; Chen, J.; Brosofske, K.D.; Saunders, S.C.; Euskirchen, E.S.; Roberts, D.; Jaiteh, M.S.; Esseen, P.-A. Edge influence on forest structure and composition in fragmented landscapes. Conserv. Biol. 2005, 19, 768–782. [Google Scholar] [CrossRef]
  11. Laurance, W.F.; Lovejoy, T.E.; Vasconcelos, H.L.; Bruna, E.M.; Didham, R.K.; Stouffer, P.C.; Gascon, C.; Bierregaard, R.O.; Laurance, S.G.; Sampaio, E. Ecosystem decay of Amazonian forest fragments: A 22-year investigation. Conserv. Biol. 2002, 16, 605–618. [Google Scholar] [CrossRef] [Green Version]
  12. Nascimento, H.E.; Laurance, W.F. Biomass dynamics in Amazonian forest fragments. Ecol. Appl. 2004, 14, 127–138. [Google Scholar] [CrossRef] [Green Version]
  13. Qie, L.; Lewis, S.L.; Sullivan, M.J.; Lopez-Gonzalez, G.; Pickavance, G.C.; Sunderland, T.; Ashton, P.S.; Hubau, W.; Abu Salim, K.; Aiba, S.-I.; et al. Long-term carbon sink in Borneo’s forests halted by drought and vulnerable to edge effects. Nat. Commun. 2017, 8, 1966. [Google Scholar] [CrossRef]
  14. Hajjar, R.; Oldekop, J.A.; Cronkleton, P.; Newton, P.; Russell, A.J.M.; Zhou, W. A global analysis of the social and environmental outcomes of community forests. Nat. Sustain. 2021, 4, 216–224. [Google Scholar] [CrossRef]
  15. Sze, J.S.; Carrasco, L.R.; Childs, D.; Edwards, D.P. Reduced deforestation and degradation in Indigenous Lands pan-tropically. Nat. Sustain. 2022, 5, 123–130. [Google Scholar] [CrossRef]
  16. Dhanapal, G. Revisiting participatory forest management in India. Curr. Sci. 2019, 117, 1161–1166. [Google Scholar] [CrossRef]
  17. Edake, S.; Sethi, P.; Lele, Y. Mainstreaming Community-Conserved Areas (CCAs) for Biodiversity Conservation in SEPLS—A Case Study from Nagaland, India. Satoyama Initiat. Themat. Rev. 2019, 5, 139–149. [Google Scholar]
  18. Champion, H.G.; Seth, S.K. A Revised Survey of the Forest Types of India; Government of India Publications: New Delhi, India, 1968. [Google Scholar]
  19. Mishra, G.; Das, P.K.; Borajh, R.; Dutta, A. Investigation of phytosociological parameters and physicochemical properties of soil in tropical semi-evergreen forests of Eastern Himalaya. J. For. Res. 2015, 28, 513–520. [Google Scholar] [CrossRef]
  20. Bandyopadhyay, S.; Barauh, U.; Das, T.H.; Dutta, D.; Reza, S.K.; Padua, S.; Sarkar, D.; Sah, K.D.; Singh, S.K. Assessment and Mapping of Some Important Soil Parameters Including Macro and Micronutrients for the State of Nagaland Towards Optimum Utilization of Land Resources for Integrated and Sustainable Development; NBSS Publication 1080, Indian Council of Agricultural Research, National Bureau of Soil Survey and Land Use Planning: Nagpur, India, 2014. [Google Scholar]
  21. Jain, S.K.; Rao, R.R. A Handbook of Field and Herbarium Methods; Today and Tomorrow Printers and Publishers: New Delhi, India, 1977. [Google Scholar]
  22. Shannon, C.E.; Wiener, W. The Mathematical Theory of Communication; University of Illinois Press: Urbana, IL, USA, 1963. [Google Scholar]
  23. Sørenson, T. A method of establishing group of equal amplitude in plant sociology based on similarity of the species content. K. Dan. Vidensk. Selsk. Skrifter. Cph. 1948, 5, 1–34. [Google Scholar]
  24. ter Braak, C.J.F.; Šmilauer, P. Canoco Reference Manual and User’s Guide, Version 5.10; Software for Ordination; Microcomputer Power: Ithaca, NY, USA, 2018. [Google Scholar]
  25. Walkley, A.; Black, I.A. 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, 29–38. [Google Scholar] [CrossRef]
  26. Nath, A.J.; Tiwari, B.K.; Sileshi, G.W.; Sahoo, U.K.; Brahma, B.; Deb, S.; Devi, N.B.; Das, A.K.; Reang, D.; Chaturvedi, S.S.; et al. Allometric models for estimation of forest biomass in Northeast India. Forests 2019, 10, 103. [Google Scholar] [CrossRef] [Green Version]
  27. ICRAF. Functional Attributes and Ecological Database. Available online: http://db.worldagroforestry.org/wd (accessed on 17 July 2022).
  28. Cairns, M.A.; Brown, S.; Helmer, E.H.; Baumgardner, G.A. Root biomass allocation in the world’s upland forests. Oecologia 1997, 111, 1–11. [Google Scholar] [CrossRef]
  29. Martin, A.R.; Doraisami, M.; Thomas, S.C. Global patterns in wood carbon concentration across the world’s trees and forests. Nat. Geosci. 2018, 11, 915–920. [Google Scholar] [CrossRef]
  30. Ali, A.; Xu, M.S.; Zhao, Y.T.; Zhang, Q.Q.; Zhou, L.L.; Yang, X.D.; Yan, E.R. Allometric biomass equations for shrub and small tree species in subtropical China. Silva Fenn. 2015, 49, 1275. [Google Scholar] [CrossRef] [Green Version]
  31. Hajjar, R.; Oldekop, J.A. Research frontiers in community forest management. Curr. Opin. Environ. Sustain. 2018, 32, 119–125. [Google Scholar] [CrossRef]
  32. Pagdee, A.; Kim, Y.-S.; Daugherty, P.J. What makes community forest management successful: A meta-study from community forests throughout the world. Soc. Nat. Resour. 2006, 19, 33–52. [Google Scholar] [CrossRef]
  33. Malhotra, K.C.; Gokhale, Y.; Chatterjee, S.; Srivastava, S. Cultural and Ecological Dimensions of Sacred Groves in India; Indian National Science Academy and Indira Gandhi Rashtriya Manav Sangrahalaya: New Delhi/Bhopal, India, 2001. [Google Scholar]
  34. Spies, T.A. Ecological concepts and diversity of old-growth forests. J. For. 2004, 102, 14–20. [Google Scholar]
  35. Tabarelli, M.; Lopes, A.V.; Peres, C.A. Edge-effects drive tropical forest fragments towards an early-successional system. Biotropica 2008, 40, 657–661. [Google Scholar] [CrossRef]
  36. Valladares, F.; Laanisto, L.; Niinemets, Ü.; Zavala, M.A. Shedding light on shade: Ecological perspectives of understorey plant life. Plant Ecol. Divers. 2016, 9, 237–251. [Google Scholar] [CrossRef] [Green Version]
  37. Baboo, B.; Sagar, R.; Bargali, S.S.; Verma, H. Tree species composition, regeneration and diversity of an Indian dry tropical forest protected area. Trop. Ecol. 2017, 58, 409–423. [Google Scholar]
  38. Mishra, B.P.; Sangma, T.M. Effect of disturbance on diversity and distribution of herbaceous vegetation in Nokrek-Biosphere Reserve, Meghalaya, Northeast India. Environ. Ecol. 2019, 37, 1186–1196. [Google Scholar]
  39. Naidu, M.T.; Kumar, O.A. Tree diversity, stand structure and community composition of tropical forest in Eastern Ghats of Andhra Pradesh, India. J. Asia-Pac. Biodivers. 2016, 9, 328–334. [Google Scholar] [CrossRef] [Green Version]
  40. Suchiang, B.R.; Nonghuloo, I.M.; Kharbhih, S.; Singh, P.P.; Tiwary, R.; Adhikari, D.; Upadhaya, K.; Ramanujam, P.; Barik, S.K. Tree diversity and community composition in sacred forests are superior than the other community forests in a human-dominated landscape of Meghalaya. Trop. Ecol. 2020, 61, 84–105. [Google Scholar] [CrossRef]
  41. Diserud, O.H.; Odegaard, F. A multiple-site similarity measure. Biol. Lett. 2007, 3, 20–22. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  42. Davidar, P.; Arjunan, M.; Mammen, P.C.; Garrigues, J.P.; Puyravaud, J.P.; Roessingh, K. Forest degradation in the Western Ghats biodiversity hotspot: Resource collection, livelihood concerns and sustainability. Curr. Sci. 2007, 93, 1573–1578. [Google Scholar]
  43. Wu, J.; Liu, Z.; Qian, J. Non-linear effect of habitat fragmentation on plant diversity: Evidence from a sand dune field in desertified grassland in northeastern China. Ecol. Eng. 2013, 54, 90–96. [Google Scholar] [CrossRef]
  44. Mylliemngap, W.; Nath, D.; Barik, S.K. Changes in vegetation and nitrogen mineralization during recovery of a montane subtropical broadleaved forest in Northeastern India following anthropogenic disturbance. Ecol. Res. 2016, 31, 21–38. [Google Scholar] [CrossRef]
  45. Singh, S.B.; Mishra, B.P.; Tripathi, S.K. Recovery of plant diversity and soil nutrients during stand development in subtropical forests of Mizoram, Northeast India. Biodiversitas 2015, 16, 205–212. [Google Scholar] [CrossRef]
  46. Sellan, G.; Simini, F.; Maritan, A.; Banavar, J.R.; de Haulleville, T.; Bauters, M.; Doucet, J.L.; Beeckman, H.; Anfodillo, T. Testing a general approach to assess the degree of disturbance in tropical forests. J. Veg. Sci. 2017, 28, 659–668. [Google Scholar] [CrossRef]
  47. Rath, S.; Bannerjee, S.; John, R. Greater tree community structure complexity in sacred forest compared to reserve forest land tenure systems in eastern India. Environ. Conserv. 2020, 47, 52–59. [Google Scholar] [CrossRef]
  48. Deb, D.; Deb, S.; Debbarma, P.; Banik, B. Impact of disturbance on vegetation, biomass and carbon stock in tropical forests of Tripura, Northeast India. Vegetos 2020, 33, 187–193. [Google Scholar] [CrossRef]
  49. Borah, N.; Nath, A.J.; Das, A.K. Aboveground biomass and carbon stocks of tree species in tropical forests of Cachar District, Assam, Northeast India. Int. J. Ecol. Environ. Sci. 2013, 39, 97–106. [Google Scholar]
  50. Borah, M.; Das, D.; Kalita, J. Tree species composition, biomass and carbon stocks in two tropical forest of Assam. Biomass Bioenergy 2015, 78, 25–35. [Google Scholar] [CrossRef]
  51. Hrahsel, L.; Sahoo, S.S.; Singh, S.L.; Sahoo, U.K. Assessment of plant diversity and carbon stock of a sub-tropical forest stand of Mizoram, India. Environ. Ecol. 2017, 37, 229–237. [Google Scholar]
  52. Niirou, N.; Gupta, A. Phytosociological analysis and carbon stocks for trees in different land uses in Senapati district of Manipur, India. Pleione 2017, 11, 64–70. [Google Scholar]
  53. Sahoo, U.K.; Tripathi, O.P.; Nath, A.J.; Deb, S.; Das, D.J.; Gupta, A.; Devi, N.B.; Charturvedi, S.S.; Singh, S.L.; Kumar, A.; et al. Quantifying tree diversity, carbon stocks, and sequestration potential for diverse land uses in Northeast India. Front. Environ. Sci. 2021, 9, 724950. [Google Scholar] [CrossRef]
  54. Thokchom, A.; Yadava, P.S. Biomass and carbon stock along an altitudinal gradient in the forest of Manipur, Northeast India. Trop. Ecol. 2017, 58, 389–396. [Google Scholar]
  55. Waikhom, A.C.; Nath, A.J.; Yadava, P.S. Aboveground biomass and carbon stock in the largest sacred grove of Manipur, Northeast India. J. For. Res. 2018, 29, 425–428. [Google Scholar] [CrossRef]
  56. Chaplin-Kramer, R.; Ramler, I.; Sharp, R.; Haddad, N.M.; Gerber, J.S.; West, P.; Mandle, L.; Engstrom, P.; Baccini, A.; Sim, S.; et al. Degradation in carbon stocks near tropical forest edges. Nat. Commun. 2015, 6, 10158. [Google Scholar] [CrossRef] [Green Version]
  57. Brahma, B.; Nath, A.J.; Sileshi, G.W.; Das, A.K. Estimating biomass stocks and potential loss of biomass carbon through clear-felling of rubber plantations. Biomass Bioenergy 2018, 115, 88–96. [Google Scholar] [CrossRef]
  58. Solomon, N.; Birhane, E.; Tadesse, T.; Treydte, A.C.; Meles, K. Carbon stocks and sequestration potential of dry forests under community management in Tigray, Ethiopia. Ecol. Process. 2017, 6, 20. [Google Scholar] [CrossRef] [Green Version]
  59. Lalnunzira, C.; Tripathi, S.K. Leaf and root production, decomposition and fluxes of carbon and nitrogen during stand development in tropical moist forests of northeast India. Soil Res. 2018, 56, 306–317. [Google Scholar] [CrossRef]
  60. Singha, D.; Brearley, F.Q.; Tripathi, S.K. Fine root and soil nitrogen dynamics during stand development following shifting agriculture in northeast India. Forests 2020, 11, 1236. [Google Scholar] [CrossRef]
  61. Brearley, F.Q.; Thomas, A.D. Land-Use Change Impacts on Soil Processes: Tropical and Savannah Environments; CABI: Wallingford, UK, 2015. [Google Scholar]
  62. Sahoo, U.K.; Singh, S.L.; Gogoi, A.; Kenye, A.; Sahoo, S.S. Active and passive soil organic carbon pools as affected by different land use types in Mizoram, Northeast India. PLoS ONE 2019, 14, e0219969. [Google Scholar] [CrossRef] [PubMed]
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Figure 1. Map of the study site and villages surrounding the Minkong Community Reserve Forest, Mokokchung district, Nagaland, India.
Figure 1. Map of the study site and villages surrounding the Minkong Community Reserve Forest, Mokokchung district, Nagaland, India.
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Figure 2. Detrended correspondence analysis ordination of (a) tree, (b) shrub, and (c) herb species in the core (filled circles) and buffer (open circles) zones in Minkong Community Forest Reserve, Nagaland, India. The comparative size of the circles represents the species richness of each plot.
Figure 2. Detrended correspondence analysis ordination of (a) tree, (b) shrub, and (c) herb species in the core (filled circles) and buffer (open circles) zones in Minkong Community Forest Reserve, Nagaland, India. The comparative size of the circles represents the species richness of each plot.
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Figure 3. Dominance–diversity curve for trees, shrubs, and herbs in core (left) and buffer (right) zones in Minkong Community Forest Reserve, Nagaland, India.
Figure 3. Dominance–diversity curve for trees, shrubs, and herbs in core (left) and buffer (right) zones in Minkong Community Forest Reserve, Nagaland, India.
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Figure 4. Contribution of tree stand density and basal area based on diameter class distributions in the core (a) and buffer (b) zones in Minkong Community Forest Reserve, Nagaland, India.
Figure 4. Contribution of tree stand density and basal area based on diameter class distributions in the core (a) and buffer (b) zones in Minkong Community Forest Reserve, Nagaland, India.
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Figure 5. Tree biomass distribution in various DBH classes for the core and buffer zones in Minkong Community Forest Reserve, Nagaland, India.
Figure 5. Tree biomass distribution in various DBH classes for the core and buffer zones in Minkong Community Forest Reserve, Nagaland, India.
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Table
Table 1. Structural attributes and diversity (mean ± standard error) of trees, shrubs, and herbs in core and buffer zones of Minkong Community Reserve Forest, Nagaland, India.
Table 1. Structural attributes and diversity (mean ± standard error) of trees, shrubs, and herbs in core and buffer zones of Minkong Community Reserve Forest, Nagaland, India.
Parameter Core ZoneBuffer Zonep-Value
No. of speciesTrees9.47 ± 0.986.33 ± 0.550.01
Shrubs7.60 ± 0.6012.1 ± 0.70<0.001
Herbs6.60 ± 0.4310.5 ± 0.850.001
Density (ind. ha−1)Trees303 ± 2.20197 ± 1.100.01
Shrubs2530 ± 21.54470 ± 14.8<0.001
Herbs35,500 ± 13250,200 ± 2670.004
Basal area (m2 ha−1)Trees32.6 ± 5.7122.2 ± 4.300.09
Shannon–Wiener diversity index (H’)Trees2.11 ± 0.100.72 ± 0.100.01
Shrubs1.85 ± 0.102.39 ± 0.05<0.001
Herbs1.73 ± 0.062.19 ± 0.07<0.001
Table
Table 2. Density (individuals ha−1), basal area (m2 ha−1), and important value index (IVI) of trees, shrubs, and herbs in core and buffer zone of Minkong Community Reserve Forest, Nagaland, India.
Table 2. Density (individuals ha−1), basal area (m2 ha−1), and important value index (IVI) of trees, shrubs, and herbs in core and buffer zone of Minkong Community Reserve Forest, Nagaland, India.
SpeciesFamilyCore ZoneBuffer Zone
DensityBasal AreaIVIDensityBasal AreaIVI
Trees
Acer thomsonii Miq.Sapindaceae13.31.1613.6
Actinodaphne obovata (Nees) Blume Lauraceae 6.670.528.94
Aglaia spectabilis (Miq.) S.S.Jain & S.Bennet Meliaceae8.330.818.05
Alnus nepalensis D.DonBetulaceae10.01.8612.5
Bauhinia purpurea L.Fabaceae 8.330.6611.5
Beilschmiedia roxburghiana NeesLauraceae 8.330.559.92
Betula alnoides Buch.-Ham. ex. D.DonBetulaceae10.02.5415.4
Bischofia javanica BlumePhyllanthaceae11.71.4411.88.330.8113.2
Brassaiopsis hainla (Buch.-Ham.) Seem.Araliaceae3.330.363.61
Callicarpa arborea Roxb.Lamiaceae8.330.697.71
Castanopsis indica (Roxb. ex Lindl.) A.DC. Fagaceae15.01.0512.410.02.7220.5
Castanopsis tribuloides (Sm.) A.DC.Fagaceae 8.330.499.64
Cephalotaxus griffithii Hook.f.Taxaceae11.71.299.21
Choerospondias axillaris (Roxb.) B.L.Burtt & A.W.HillAnacardiaceae15.01.3015.3
Cinnamomum sulphuratum NeesLauraceae10.00.448.20
Cinnamomum verum J.Presl.Lauraceae15.00.7410.86.670.326.95
Dalrympelea pomifera Roxb.Staphyleaceae 10.00.7412.7
Elaeocarpus tectorius (Lour.) Poir.Elaeocarpaceae11.71.3111.4
Engelhardia spicata Lechen ex BlumeJuglandaceae 8.330.7012.7
Eurya cerasifolia (D.Don) KobuskiPentaphylacaceae 8.330.4810.7
Ficus hispida L.f.Moraceae5.000.374.908.330.209.41
Ficus neriifolia Sm.Moraceae 5.000.256.85
Ficus semicordata Buch.-Ham. ex Sm.Moraceae16.70.8713.83.330.204.71
Garcinia pedunculata Roxb. ex Buch.-Ham.Clusiaceae16.71.5815.3
Grewia serrulata DC.Malvaceae3.330.313.48
Hovenia dulcis Thunb.Rhamnaceae8.331.038.73
Ilex sp.Aquifoliaceae3.330.102.83
Ilex dipyrena Wall.Aquifoliaceae 10.01.1315.5
Juglans regia L.Juglandaceae11.71.4912.7
Lithocarpus elegans (Blume) Hatus. ex SoepadmoFagaceae10.01.9012.016.73.0131.6
Lithocarpus pachyphyllus (Kurz) RehderFagaceae16.71.0215.0
Macaranga denticulata (Blume) Müll.Arg.Euphorbiaceae 11.70.7515.7
Macropanax dispermus (Blume) KuntzeAraliaceae10.00.968.38
Mallotus nepalensis Müll.Arg.Euphorbiaceae8.330.456.24
Morus macroura var. macroura Miq.Moraceae 13.32.2822.4
Myrica esculenta Buch.-Ham. ex D.DonMyricaceae6.670.446.37
Oreocnide integrifolia (Gaudich.) Miq. Urticaceae3.330.203.13
Prunus napaulensis (Ser.) Steud.Rosaceae 5.002.0414.9
Quercus lamellosa Sm.Fagaceae5.002.5211.5
Quercus serrata MurrayFagaceae13.31.1111.38.330.8312.2
Sloanea dasycarpa (Benth.) Hemsl.Elaeocarpaceae 11.70.6216.2
Sterculia lanceolata var. coccinea (Jack) PhengklaiSterculiaceae 11.70.7115.5
Terminalia myriocarpa Van Heurck & Müll.Arg.Combretaceae10.01.3310.2
Toona ciliata M.Roem.Meliaceae5.001.668.16
Trema cannabina Lour. Cannabaceae6.670.305.94
Xerospermum noronhianum (Blume) BlumeSapindaceae 8.332.2118.5
Shrubs
Abutilon indicum (L.) SweetMalvaceae 120 3.78
Agapetes macrantha (Hook.) Benth. & Hook.f.Ericaceae 160 6.86
Amomum dealbatum Roxb.Zingiberaceae 147 8.20
Boehmeria japonica (L.f.) Miq.Urticaceae213 15.5200 10.5
Breynia retusa (Dennst.) AlstonPhyllanthaceae 173 6.61
Calamus rotang L.Arecaceae93.3 7.22
Camellia oleifera C.AbelTheaceae 173 7.16
Chromolaena odorata (L.) R.M.King & H.Rob.Asteraceae160 9.85240 9.20
Clerodendrum glandulosum Lindl.Lamiaceae280 21.7107 4.57
Crotalaria juncea L.Fabaceae120 8.28
Croton caudatus Geiseler Euphorbiaceae147 12.0
Debregeasia longifolia (Burm.f.) Wedd.Urticaceae 173 7.71
Dendrocnide sinuata (Blume) Chew.Urticaceae133 10.6227 11.6
Deutzia compacta CraibHydrangeaceae80.0 7.58
Eriosolena involucrata (Wall.) Tiegh.Thymelaeaceae160 16.9
Grona heterocarpos (L.) H.Ohashi & K.OhashiFabaceae 213 9.69
Hibiscus sabdariffa L.Malvaceae 93.3 4.28
Leucosceptrum canum Sm.Lamiaceae187 11.8200 8.30
Maesa indica (Roxb.) SweetPrimulaceae147 9.33
Melastoma malabathricum L.Melastomataceae120 11.8240 9.75
Millettia pachycarpa Benth.Fabaceae173 15.7
Mussaenda roxburghii Hook.f.Rubiaceae93.3 8.99227 9.45
Neillia thyrsiflora D.DonRosaceae 133 7.36
Osbeckia nepalensis Hook.Melastomataceae 293 13.7
Oxalis acetosella L.Oxalidaceae 133 5.72
Oxyspora paniculata (D.Don) DC.Melastomataceae 200 8.30
Rhaphiolepis bengalensis (Roxb.) B.B.Liu & J.WenRosaceae93.3 8.11173 7.71
Rubus ellipticus Sm.Rosaceae 213 9.69
Rubus efferatus CraibRosaceae40.0 4.23133 5.72
Rubus lucens FockeRosaceae 187 11.3
Securinega sp.Phyllanthaceae 240 9.75
Senegalia pennata (L.) MaslinFabaceae120 10.166.7 3.13
Uraria oblonga (Wall. ex Benth.) H.Ohashi & K.OhashiFabaceae173 10.4
Herbs
Arisaema concinnum SchottAraceae667 3.802170 10.7
Bidens pilosa L.Asteraceae1330 7.601670 6.49
Commelina benghalensis L.Commelinaceae4000 16.13170 12.6
Curculigo orchioides Gaertn.Hypoxidaceae 2500 12.6
Cymbidium aloifolium (L.) Sw. Orchidaceae1830 9.972170 8.75
Dendrobium lituiflorum Lindl.Orchidaceae 2330 11.0
Dioscorea glabra Roxb.Dioscoreaceae100 4.742500 10.1
Drymaria cordata (L.) Willd. ex Schult.Caryophyllaceae1670 7.58
Elatostema sessile J.R.Forst. & G.Forst.Urticaceae2330 12.31170 4.86
Entada rheedei Spreng.Fabaceae1170 5.211000 5.16
Erythropalum scandens BlumeOlacaceae833 3.31
Fagopyrum cymosum (Trevir.) Meisn. Polygonaceae 2670 9.11
Fragaria nilgerrensis Schltdl. ex J.GayRosaceae1670 7.582330 8.45
Girardinia diversifolia (Link) FriisUrticaceae4170 22.32170 6.85
Gnetum latifolium BlumeGnetaceae1500 9.991830 6.19
Gomphostemma strobilinum Wall. ex Benth.Lamiaceae1670 9.503830 12.1
Hedychium coronarium J.KoenigZingiberaceae 1330 6.45
Hellenia speciosa (J.Koenig) S.R.Dutta Costaceae1500 12.93670 12.4
Mucuna macrocarpa Wall.Fabaceae1330 8.562330 10.4
Oxalis corniculata L.Oxalidaceae833 5.23
Papilionanthe teres (Roxb.) Schltr. Orchidaceae1500 13.8
Phanera vahlii (Wight & Arn.) Benth.Fabaceae2000 12.41330 4.56
Poranopsis paniculata (Roxb.) Roberty Convolvulaceae2330 9.462830 10.1
Saccharum longesetosum (Andersson) V.Naray. ex BorPoaceae 1000 3.89
Smilax aspera L.Smilacaceae2170 17.61170 5.49
Spatholobus parviflorus (Roxb. ex G.Don) KuntzeFabaceae 2330 11.6
Tetrastigma eucostaphylum (Dennst.) Alston Vitaceae 667 2.59
Tinospora sinensis (Lour.) Merr. Menispermaceae 2000 7.78
Table
Table 3. Total biomass (Mg ha−1) (mean ± standard error) in core and buffer zones of Minkong Community Reserve Forest, Nagaland, India).
Table 3. Total biomass (Mg ha−1) (mean ± standard error) in core and buffer zones of Minkong Community Reserve Forest, Nagaland, India).
Ecosystem ComponentCore ZoneBuffer Zone
Above-ground tree biomass263 ± 8.4177 ± 11
Below-ground tree biomass58.7 ± 3.440.7 ± 4.1
Shrub biomass1.20 ± 1.22.01 ± 0.3
Herb biomass0.70 ± 0.60.93 ± 0.4
Floor mass 3.3 ± 0.83.4 ± 0.5
Total stand biomass 327 ± 13.3224 ± 18.7
Table
Table 4. Distribution of carbon stocks (Mg C ha−1) (mean ± standard error) in different ecosystem compartments of core and buffer zone of Minkong Community Forest Reserve, Nagaland, India.
Table 4. Distribution of carbon stocks (Mg C ha−1) (mean ± standard error) in different ecosystem compartments of core and buffer zone of Minkong Community Forest Reserve, Nagaland, India.
Ecosystem CompartmentCore ZoneBuffer Zone
Above-ground tree biomass120 ± 0.3180.7 ± 0.43
Below-ground tree biomass26.8 ± 1.4518.6 ± 2.10
Shrub biomass0.54 ± 1.160.92 ± 0.52
Herb biomass0.31 ± 1.200.42 ± 0.45
Floor mass1.50 ± 0.121.55 ± 0.15
Total biomass carbon149 ± 3.40102 ± 1.21
Soil organic carbon75 ± 4.5171 ± 3.45
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Ao, A.; Changkija, S.; Brearley, F.Q.; Tripathi, S.K. Plant Community Composition and Carbon Stocks of a Community Reserve Forest in North-East India. Forests 2023, 14, 245. https://doi.org/10.3390/f14020245

AMA Style

Ao A, Changkija S, Brearley FQ, Tripathi SK. Plant Community Composition and Carbon Stocks of a Community Reserve Forest in North-East India. Forests. 2023; 14(2):245. https://doi.org/10.3390/f14020245

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Ao, Aosanen, Sapu Changkija, Francis Q. Brearley, and Shri Kant Tripathi. 2023. "Plant Community Composition and Carbon Stocks of a Community Reserve Forest in North-East India" Forests 14, no. 2: 245. https://doi.org/10.3390/f14020245

APA Style

Ao, A., Changkija, S., Brearley, F. Q., & Tripathi, S. K. (2023). Plant Community Composition and Carbon Stocks of a Community Reserve Forest in North-East India. Forests, 14(2), 245. https://doi.org/10.3390/f14020245

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