Future socioeconomic induced climate scenarios may lead to decline in Cinnamomum glaucescens (Nees) Hand.-Mazz population in the Himalayan region
Pramod Chand Lakra
ICFRE - Institute of Forest Productivity, Ranchi-835303, Jharkhand, INDIA
Sonu Choudhary
ICFRE - Institute of Forest Productivity, Ranchi-835303, Jharkhand, INDIA
https://orcid.org/0009-0007-4092-9294
Sanjoy Garai
ICFRE - Institute of Forest Productivity, Ranchi-835303, Jharkhand, INDIA
Surojit Konar
ICFRE - Institute of Forest Productivity, Ranchi-835303, Jharkhand, INDIA
Shibnarayan Pratihar
ICFRE - Institute of Forest Productivity, Ranchi-835303, Jharkhand, INDIA
Raju Sharma
ICFRE - Institute of Forest Productivity, Ranchi-835303, Jharkhand, INDIA
Basant Kumar
ICFRE - Institute of Forest Productivity, Ranchi-835303, Jharkhand, INDIA
https://orcid.org/0009-0008-0325-8206
V Rathna
ICFRE - Institute of Wood Science and Technology, Bengaluru, INDIA
Sharad Tiwari
ICFRE - Institute of Forest Productivity, Ranchi-835303, Jharkhand, INDIA
https://orcid.org/0000-0003-4902-8349
DOI: https://doi.org/10.59429/ce.v2i2.10401
Keywords: Cinnamomum glaucescens, climate change, habitat shift, Himalayan region, shared socioeconomic pathways
Abstract
The natural population of Cinnamomum glaucescens is declining due to anthropogenic stress and climate change in the Himalayan region. We assessed the potential suitable habitat range of C. glaucescens in the North Bengal region, under current and future climate scenarios using Maxent. Two climate models, Institut Pierre-Simon Laplace (IPSL-CM6A-LR) and Model for Interdisciplinary Research on Climate 6 (MIROC6) proxied through the Shared Socioeconomic Pathways (SSP) SSP126, 245,370, and 585 were employed to project future climate scenarios for 2050. The study found that currently 1,302 square kilometers, or ~ 9% of the total study area, comprising the central and northern parts of North Bengal are potentially suitable for the distribution of C. glaucescens. The distribution was found up to 1900m elevation range. Depending upon the climate scenario, by 2050, the potential suitable habitat of C. glaucescens might decline in the range of ~7-22% (IPSL_6A_LR), and ~39-70 % (MIROC6) across all the SSPs. Overall, the suitable habitat range of C. glaucescens might be limited to ~ 6% of the total geographical area of Northern Bengal by 2050. The suitable habitat of C. glaucescens is predicted to shift northward by 2050, leading to significant decline from the central part of the region. Out of nine bioclimatic variables used for the modelling the habitat suitability, Precipitation of the warmest quarter (Bio_18) and annual precipitation (Bio_12) contributed most to limiting the distribution of C. glaucescens. We recommend establishing a germplasm bank and adopting in-situ and ex-situ approaches to conserve and promote C. glaucescens in the Himalayan region.
References
1.Barua A, Bhaduri R, Gulati V, Dasgupta S, Sanyal K, Alam MK, et al. Climate vulnerability assessment for the Indian Himalayan region using a common framework. 2020.
2.Wani IA, Khan S, Verma S, Al-Misned FA, Shafik HM, El-Serehy HA, et al. Predicting habitat suitability and niche dynamics of Dactylorhiza hatagirea and Rheum webbianum in the Himalaya under projected climate change. Sci Rep. 2022;12(1):1-18. https://doi.org/10.1038/s41598-022-16837-5.
3.Sharma P, Acharya KR. Economics of Cinnamomum glaucescens (Nees.) Drury in Western Terai Region of Nepal: A value chain perspective. Forestry: Journal of Institute of Forestry, Nepal. 2020;17:102-17. https://doi.org/10.3126/forestry.v17i0.33625.
4.Negi GCS, Rawal RS. Himalayan biodiversity in the face of climate change. In: Tropical Ecosystems: Structure, Functions and Challenges in the Face of Global Change. Singapore: Springer; 2019. p. 263-77. https://doi.org/10.1007/978-981-13-8249-9_14.
5.Chettri N, Tsering K, Shrestha A, Sharma E. Ecological vulnerability to climate change in the mountains: A case study from the Eastern Himalayas. Google Scholar. 2018:707-21.
6.Singh H, Kumar M. Climate change and its impact on Indian Himalayan forests: Current status and research needs. In: Climate Change. Cham: Springer; 2022. p. 223-42. https://doi.org/10.1007/978-3-030-92782-0_11.
7.Taheri S, Naimi B, Rahbek C, Araújo MB. Improvements in reports of species redistribution under climate change are required. Sci Adv. 2021;7(15):eabe1110. https://doi.org/10.1126/sciadv.abe1110.
8.Holzel N, Hickler T, Kutzbach L, Joosten H, Huissteden JV, Hiederer R. Environmental impacts—terrestrial ecosystems. In: North Sea region climate change assessment. Cham: Springer; 2016. p. 341-72. https://doi.org/10.1007/978-3-319-39745-0.
9.Hillebrand H, Brey T, Gutt J, Hagen W, Metfies K, Meyer B, et al. Climate change: Warming impacts on marine biodiversity. In: Handbook on marine environment protection. Cham: Springer; 2018. p. 353-73. https://doi.org/10.1007/978-3-319-60156-4_18.
10.Wessely J, Gattringer A, Guillaume F, Hülber K, Klonner G, Moser D, et al. Climate warming may increase the frequency of cold-adapted haplotypes in alpine plants. Nat Clim Change. 2022;12(1):77-82. https://doi.org/10.1038/s41558-021-01255-8.
11.Ravindran PN, Nirmal-Babu K, Shylaja M, editors. Cinnamon and Cassia: The genus Cinnamomum. Boca Raton, Florida: CRC Press; 2003.
12.Sthapit VM, Tuladhar PM. Sugandha kokila oil: A gift to perfumers from the Himalayan Kingdom of Nepal. J Herbs Spices Med Plants. 1993;1(4):31-5. https://doi.org/10.1300/J044v01n04_06.
13.Tiwari S, Upadhyay N, Singh BK, Singh VK, Dubey NK. Facile fabrication of nanoformulated Cinnamomum glaucescens essential oil as a novel green strategy to boost potency against food borne fungi, aflatoxin synthesis, and lipid oxidation. Food Bioprocess Technol. 2022;15(2):319-37. https://doi.org/10.1007/s11947-021-02739-3.
14.Finnemore H. The Essential Oils. London: Ernest Benn Ltd; 1926.
15.Rani A, Pande C, Tewari G, Patni K. A review on aroma profile of Cinnamomum species in north and north east India. World J Pharm Res. 2017;6(11):200-21. http://dx.doi.org/10.20959/wjpr201711-9501.
16.Royal Botanic Gardens, Kew, Plants of the World Online. Cinnamomum glaucescens (Nees) Hand.-Mazz. First published in Oesterr Bot Z. 1936;85:214. Accessed on 18 July 2023. https://powo.science.kew.org/taxon/urn:lsid:ipni.org:names:463436-1.
17.De Kok R. Cinnamomum glaucescens. The IUCN Red List of Threatened Species 2022:e.T145309203A145416036. Accessed on 29 August 2022. https://dx.doi.org/10.2305/IUCN.UK.2022-1.RLTS.T145309203A145416036.en.
18.Chakraborty A, Joshi PK, Sachdeva K. Predicting distribution of major forest tree species to potential impacts of climate change in the central Himalayan region. Ecol Eng. 2016;97:593-609. https://doi.org/10.1016/j.ecoleng.2016.10.006.
19.Malhi Y, Franklin J, Seddon N, Solan M, Turner MG, Field CB, et al. Climate change and ecosystems: Threats, opportunities and solutions. Phil Trans R Soc B. 2020;375(1794):20190104. https://doi.org/10.1098/rstb.2019.0104.
20.Tanaka N, Nakao K, Tsuyama I, Higa M, Nakazono E, Matsui T. Predicting the impact of climate change on potential habitats of fir (Abies) species in Japan and on the East Asian continent. Procedia Environ Sci. 2012;13:455-66. https://doi.org/10.1016/j.proenv.2012.01.039.
21.Nagendra, H., Paul, S., Pareeth, S., & Dutt, S. (2009). Landscapes of protection: forest change and fragmentation in Northern West Bengal, India. Environmental Management, 44(5), 853-864.
22.Karmakar M. Ecotourism and its impact on the regional economy: A study of North Bengal (India). Tourismos. 2011;6(1):251-70. https://doi.org/10.26215/tourismos.v6i1.207.
23.Das J, Mandal T, Saha P. Spatio-temporal trend and change point detection of winter temperature of North Bengal, India. Spatial Inf Res. 2019;27:411-24. https://doi.org/10.1007/s41324-019-00241-9.
24.Mukherjee D. Resource conservation through indigenous farming system in hills of West Bengal. J Crop Weed. 2012;8(1):160-4.
25.Fick SE, Hijmans RJ. WorldClim 2: New 1-km spatial resolution climate surfaces for global land areas. Int J Climatol. 2017;37(12):4302-15. https://doi.org/10.1002/joc.5086.
26.Sharma J, Singh R, Garai S, Rahaman SM, Khatun M, Ranjan A, et al. Climate change and dispersion dynamics of the invasive plant species Chromolaena odorata and Lantana camara in parts of central and eastern India. Ecol Inform. 2022;72:101824. https://doi.org/10.1016/j.ecoinf.2022.101824.
27.Profirio LL, Harris RMB, Lefroy EC, et al. Improving the use of species distribution models in conservation planning and management under climate change. PLoS ONE. 2014;9(11):e113749. https://doi.org/10.1371/journal.pone.0113749.
28.Plisson F, Piggott AM. Predicting blood–brain barrier permeability of marine-derived kinase inhibitors using ensemble classifiers reveals potential hits for neurodegenerative disorders. Mar Drugs. 2019;17(2):81. https://doi.org/10.3390/md17020081.
29.Phillips SJ, Dudik M, Schapire RE. Maxent software for modeling species niches and distributions (version 3.4.4). Available from: https://biodiversityinformatics.amnh.org/open_source/maxent/. Accessed on 10 October 2022.
30.Padalia H, Srivastava V, Kushwaha SPS. Modeling potential invasion range of alien invasive species, Hyptis suaveolens (L.) Poit. in India: Comparison of MaxEnt and GARP. Eco Inform. 2014;22:36-43. https://doi.org/10.1016/j.ecoinf.2014.04.002.
31.Young N, Carter L, Evangelista P. A MaxEnt model v3.3.3e tutorial (ArcGIS v10). Natural Resource Ecology Laboratory, Colorado State University and the National Institute of Invasive Species Science; 2011.
32.Fielding AH, Bell JF. A review of methods for the assessment of prediction errors in conservation presence/absence models. Environ Conserv. 1997;24(1):38-49. https://doi.org/10.1017/S0376892997000088.
33.ESRI LULC. Powered by Esri. Sentinel-2 10m Land Use/Land Cover data by Impact Observatory, Microsoft, and Esri. 2022.
34.Mohammad N, Rahaman SM, Khatun M, Rajkumar M, Garai S, Ranjan A, et al. Teak (Tectona grandis Lf) demonstrates robust adaptability to climate change scenarios in central India. Vegetos. 2022;1-10. https://doi.org/10.1007/s42535-022-00444-w.
35.Yang S, Chen K, Zeng Z, Zhu B, Yin M, Tang J, et al. The effects of future climate change on hydrologic and biogeochemical cycles in a large endorheic river basin. In: AGU Fall Meeting Abstracts. 2023; Vol. 2023, No. 863, pp. GC51Q-0863.
36.Rahimian Boogar A, Salehi H, Pourghasemi HR, Blaschke T. Predicting habitat suitability and conserving Juniperus spp. habitat using SVM and maximum entropy machine learning techniques. Water. 2019;11(10):2049. https://doi.org/10.3390/w11102049.
37.Gobeyn S, Mouton AM, Cord AF, Kaim A, Volk M, Goethals PL. Evolutionary algorithms for species distribution modelling: A review in the context of machine learning. Ecol Modell. 2019;392:179-95. https://doi.org/10.1016/j.ecolmodel.2018.11.013.
38.Barooah C, Ahmed I. Assam Science Technology and Environment Council. 2014.
39.Manish K, Telwala Y, Nautiyal DC, Pandit MK. Modelling the impacts of future climate change on plant communities in the Himalaya: A case study from Eastern Himalaya, India. Model Earth Syst Environ. 2016;2:1-12. https://doi.org/10.1007/s40808-016-0163-1.
40.Garai S, Mishra Y, Malakar A, Kumar R, Singh R, Sharma J, et al. Buchanania cochinchinensis (Lour.) MR Almeida habitat exhibited robust adaptability to diverse socioeconomic scenarios in eastern India. Environ Monit Assess. 2023;195(8):1005. https://doi.org/10.1007/s10661-023-11611-0.
41.Telwala Y, Brook BW, Manish K, Pandit MK. Climate-induced elevational range shifts and increase in plant species richness in a Himalayan biodiversity epicentre. PLoS One. 2013;8(2):e57103. https://doi.org/10.1371/journal.pone.0057103.
42.Ghosh BG, Garai S, Rahaman SM, Khatun M, Mohammad N, Mishra Y, et al. Assessing potential habitat distribution range of the endangered tree species Pterocarpus marsupium Roxb. under the climate change scenario in India. Trees, Forests People. 2021;6:100124. https://doi.org/10.1016/j.tfp.2021.100124.
43.Gebrewahid Y, Abrehe S, Meresa E, Eyasu G, Abay K, Gebreab G, et al. Current and future predicting potential areas of Oxytenanthera abyssinica (A. Richard) using MaxEnt model under climate change in Northern Ethiopia. Ecol Processes. 2020;9(1):1-15. https://doi.org/10.1186/s13717-019-0210-8.
44.Singh P, Negi GCS. Impact of climate change on phenological responses of major forest trees of Kumaun Himalaya. ENVIS Bulletin, Himalayan Ecology. 2016;24:112-6.
45.Singh R, Rawat M, Chand T, Tripathi SK, Pandey R. Phenological variations in relation to climatic variables of moist temperate forest tree species of western Himalaya, India. Heliyon. 2023;9(6):e16563. https://doi.org/10.1016/j.heliyon.2023.e16563.
46.Brandt M, Rasmussen K, Penuelas J, Tian F, Schurgers G, Verger A, et al. Human population growth offsets climate-driven increase in woody vegetation in sub-Saharan Africa. Nat Ecol Evol. 2017;1(4):0081. https://doi.org/10.1038/s41559-017-0081.
47.Johnson L, Evans J, Montgomery J, Chenery C. The forest effect: Biosphere 87Sr/86Sr shifts due to changing land use and the implications for migration studies. Sci Total Environ. 2022;839:156083. https://doi.org/10.1016/j.scitotenv.2022.156083.
48.Theodorou P. The effects of urbanisation on ecological interactions. Curr Opin Insect Sci. 2022;100922. https://doi.org/10.1016/j.cois.2022.100922.
49.Vanbergen AJ, Initiative TIP. Threats to an ecosystem service: Pressures on pollinators. Front Ecol Environ. 2013;11(5):251-9. https://doi.org/10.1890/120126.
50.Nalau J, Becken S, Mackey B. Ecosystem-based adaptation: A review of the constraints. Environ Sci Policy. 2018;89:357-64. https://doi.org/10.1016/j.envsci.2018.08.014.
51.Denton F, Wilbanks TJ, Abeysinghe AC, Burton I, Gao Q, Lemos MC, et al. Climate-resilient pathways: Adaptation, mitigation, and sustainable development. Clim Change. 2014;1101-31.