Hostname: page-component-669899f699-2mbcq Total loading time: 0 Render date: 2025-04-29T04:27:37.732Z Has data issue: false hasContentIssue false

Predicted distribution of the endemic fern Elaphoglossum beddomei reveals threats to rainforests of Western Ghats of India

Published online by Cambridge University Press:  12 November 2024

R. Thulasi
Affiliation:
Department of Quality Control, National Ayurveda Research Institute for Panchakarma (under CCRAS, Ministry of AYUSH, Government of India), Thrissur, Kerala, India PG & Research Department of Botany, The Zamorin’s Guruvayurappan College (affiliated to University of Calicut), Kozhikode, Kerala 673014, India
Francois Munoz
Affiliation:
Laboratoire Interdisciplinaire de Physique, Université Grenoble-Alpes, Grenoble, France
E.R. Sreekumar
Affiliation:
Department of Wildlife Science, College of Forestry, Kerala Agricultural University, Vellanikkara, Thrissur, Kerala 680656, India
Maya C. Nair
Affiliation:
Post Graduate & Research Department of Botany, Government Victoria College (affiliated to University of Calicut), Palakkad, Kerala 678001, India Government Arts and Science College, Tholanur (affiliated to University of Calicut), Palakkad, Kerala 678722, India
K.P. Rajesh*
Affiliation:
PG & Research Department of Botany, The Zamorin’s Guruvayurappan College (affiliated to University of Calicut), Kozhikode, Kerala 673014, India
*
Corresponding author: K. P. Rajesh; Email: [email protected]

Abstract

Pteridophytes are excellent ecological indicators of habitat quality. In this study, we built a model that predicts the habitat suitability of Elaphoglossum beddomei Sledge, an epiphytic or lithophytic and endemic pteridophyte in Southern Western Ghats, by using the technique of species distribution modelling. The occurrence data of E. beddomei from field explorations as well as from various herbaria were collected during 2018–2022. These occurrence data along with climatic data were processed by R packages. The processed data were further analysed using MaxEnt software to project the distribution of E. beddomei in future climatic scenarios. After correlation analysis, five bioclimatic variables – Mean Temperature of Wettest Quarter (bio8), Precipitation of Driest Quarter (bio17), Precipitation of Warmest Quarter (bio18), Precipitation of Wettest Quarter (bio16) and Temperature Annual Range (BIO5-BIO6) (bio7) – were selected from 19 bioclimatic variables with less correlation. Precipitation of Warmest Quarter (bio18) had the most influence in determining the distribution of E. beddomei, with a permutation importance of 83%. Conversely, Temperature Annual Range (BIO5-BIO6) (bio7) and Precipitation of Driest Quarter (bio17) showed least influence in determining the distribution of E. beddomei, and hence, the models created without these variables are considered for prediction. The habitat suitability predictions of the model indicate that the potential habitats of the species may get reduced in Southern Western Ghats in future climatic scenarios. It is in tune with the predicted expansion of drier climatic zones in Southern Western Ghats, which may reduce the suitable habitats for the E. beddomei in near future. So, it demands formulating suitable strategies for reducing the emission of greenhouse gases, regenerating forests and conserving forests by implementing more stringent policies on the environment to protect such highly habitat-specific evergreen elements.

Type
Research Article
Copyright
© The Author(s), 2024. Published by Cambridge University Press

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

Article purchase

Temporarily unavailable

References

Abdelaal, M, Fois, M, Fenu, G and Bacchetta, G (2019) Using MaxEnt modeling to predict the potential distribution of the endemic plant Rosa arabica Crép. Egypt. Ecological Informatics 50, 6875.CrossRefGoogle Scholar
Antao, LH, Bates, AE, Blowes, SA, Waldock, C, Supp, SR, Magurran, AE, Dornelas, M and Schipper, AM (2020) Temperature-related biodiversity changes across temperate marine and terrestrial systems. Nature Ecology & Evolution 4, 927933.CrossRefGoogle ScholarPubMed
Arogoundade, AM, Odindi, J and Mutanga, O (2020) Modelling Parthenium hysterophorus invasion in KwaZulu-Natal province using remotely sensed data and environmental variables. Geocarto International 35, 14501465.CrossRefGoogle Scholar
Benniamin, A, Bhagathsingh, C, Sundari, MS and Jesubalan, D (2020) Spore germination and early gametophyte development of an endemic fern, Elaphoglossum beddomei Sledge. Indian Fern J 37, 246251.Google Scholar
Benniamin, A and Sundari, MS (2020) Pteridophytes of Western Ghats- A Pictorial Guide. Dehra Dun: Bishen Singh Mahendra Pal Singh.Google Scholar
Indian Biodiversity Information System https://www.indiaobservatory.org.in/tool/ibis.Google Scholar
Bose, R, Munoz, F, Ramesh, BR, et al. (2016) Past potential habitats shed light on the biogeography of endemic tree species of the Western Ghats biodiversity hotspot, South India. Journal of Biogeography 43, 899910.CrossRefGoogle Scholar
Brummitt, N, Aletrari, E, Syfert, MM, et al. (2016) Where are threatened ferns found? Global conservation priorities for pteridophytes. Journal of Systematics Evolution 54, 604616.CrossRefGoogle Scholar
Chaitanya, R and Meiri, S (2021) Can’t see the wood for the trees? Canopy physiognomy influences the distribution of peninsular Indian Flying lizards. Journal of Biogeography 49, 113.CrossRefGoogle Scholar
Chandra, S, Fraser-Jenkins, CR, Kumari, A, et al. (2008) A summary of the status of threatened pteridophytes of India. Taiwania 53, 170209.Google Scholar
Chauhan, S, Ghoshal, S, Kanwal, KS, Sharma, V and Ravikanth, G (2022) Ecological niche modelling for predicting the habitat suitability of endangered tree species Taxus contorta Griff. in Himachal Pradesh (Western Himalayas, India). Tropical Ecology 63(2), 300313.CrossRefGoogle Scholar
Choudhary, JS, Mali, SS, Fand, BB, et al. (2019) Predicting the invasion potential of indigenous restricted mango fruit borer, Citripestis eutraphera (Lepidoptera: Pyralidae) in India based on MaxEnt modelling. Current Science 25, 636.CrossRefGoogle Scholar
Choudhury, MR, Deb, P, Singha, H, et al. (2016) Predicting the probable distribution and threat of invasive Mimosa diplotricha Suavalle and Mikania micrantha Kunth in a protected tropical grassland. Ecological Engineering 1, 2331.CrossRefGoogle Scholar
Della, AP and Falkenberg, DD (2019) Pteridophytes as ecological indicators: an overview. Hoehnea 46, e522018.CrossRefGoogle Scholar
Ebihara, A, Fraser-Jenkins, CR, Parris, BS, et al. (2012) Rare and threatened pteridophytes of Asia 1. An enumeration of narrowly distributed taxa. Bull Natl Mus Nat Sci, Ser B 38, 93119.Google Scholar
Elith, J, Phillips, SJ, Hastie, T, et al. (2011) A statistical explanation of MaxEnt for ecologists. Diversity and Distributions 17, 4357.CrossRefGoogle Scholar
Escobar, LE, Lira-Noriega, A, Medina-Vogel, G, et al. (2014) Potential for spread of the white-nose fungus (Pseudogymnoascus destructans) in the Americas: use of MaxEnt and NicheA to assure strict model transference. Geospat 9, 221229.CrossRefGoogle ScholarPubMed
Ferreira, MR, Almeida, AM, Quintela-Sabarís, C, et al. (2021) The role of littoral cliffs in the niche delimitation on a microendemic plant facing climate change. PLoS One 16, 0258976.CrossRefGoogle ScholarPubMed
Fraser-Jenkins, CR (2008) Endemics and pseudo-endemics in Relation to the distribution patterns of Indian Pteridophytes. Taiwania 53, 264292.Google Scholar
Fraser-Jenkins, CR, Gandhi, KN, Kholia, BS, et al. (2021) An Annotated Checklist of Indian Pteridophytes Part 1. DehraDun: Bishen Singh Mahendra Pal Singh.Google Scholar
Hassler, M (2024) World Ferns. Synonymic Checklist and Distribution of Ferns and Lycophytes of the World. Version 18.4. Available at https://www.worldplants.de/ferns/ (accessed 9 October, 2024).Google Scholar
Holttum, R (1938) The ecology of tropical pteridophytes. In Verdoorn F (ed), Manualof Pteridology. DenHaag: Nijhoff.Google Scholar
Hsu, RC, Oostermeijer, JG and Wolf, JH (2014) Adaptation of a widespread epiphytic fern to simulated climate change conditions. Plant Ecol 1, 889897.CrossRefGoogle Scholar
Hsu, RC, Tamis, WL, Raes, N, et al. (2012) Simulating climate change impacts on forests and associated vascular epiphytes in a subtropical island of East Asia. Diversity and Distributions 18, 334347.CrossRefGoogle Scholar
Hsu, RC, Wolf, JH and Tamis, WL (2014) Regional and elevational patterns in vascular epiphyte richness on an East Asian island. Biotropica 46, 549555.CrossRefGoogle Scholar
Huang, Z, Xie, L, Wang, H, et al. (2019) Geographic distribution and impacts of climate change on the suitable habitats of Zingiber species in China. Industrial Crops and Products 5, 111429.CrossRefGoogle Scholar
Jose, SV and Nameer, PO (2020) The expanding distribution of the Indian Peafowl (Pavo cristatus) as an indicator of changing climate in Kerala, southern India: a modelling study using MaxEnt. Ecological Indicators 110, 105930.CrossRefGoogle Scholar
Joshi, M, Charles, B, Ravikanth, G, et al. (2017) Assigning conservation value and identifying hotspots of endemic rattan diversity in the Western Ghats, India. Plant Diversity 39, 263272.CrossRefGoogle ScholarPubMed
Kailash, BR, Charles, B, Ravikanth, G, Setty, S and Kadirvelu, K (2022) Identifying the potential global distribution and conservation areas for Terminalia chebula, an important medicinal tree species under changing climate scenario. Tropical Ecology 63(4), 584595.CrossRefGoogle Scholar
Karger, DN, Conrad, O, Böhner, J, et al. (2021a) Climatologies at high resolution for the earth’s land surface areas. Scientific Data 4, 170122.CrossRefGoogle Scholar
Karger, DN, Kessler, M, Lehnert, M, et al. (2021b) Limited protection and ongoing loss of tropical cloud forest biodiversity and ecosystems worldwide. Nature Ecology & Evolution 5, 854862.CrossRefGoogle ScholarPubMed
Khanum, R, Mumtaz, AS and Kumar, S (2013) Predicting impacts of climate change on medicinal asclepiads of Pakistan using MaxEnt modeling. Acta Oecol 49, 2331.CrossRefGoogle Scholar
Kumar, B (2011) Elaphoglossum Beddomei. Cambridge: The IUCN Red List of Threatened Species.Google Scholar
Laurance, WF, Useche, DC, Rendeiro, J, et al. (2012) Averting biodiversity collapse in tropical forest protected areas. Nature 489, 290294.CrossRefGoogle ScholarPubMed
Li, Y, Cao, W, He, X, et al. (2019) Prediction of suitable habitat for Lycophytes and Ferns in northeast China: a case study on Athyrium brevifrons . Chin Geogr Sci 29, 10111023.CrossRefGoogle Scholar
Liu, C, White, M and Newell, G (2013) Selecting thresholds for the prediction of species occurrence with presence-only data. Journal of Biogeography 40, 778789.CrossRefGoogle Scholar
Manickam, VS and Irudayaraj, V (1992) Pteridophyte Flora of the Western Ghats – South India. New Delhi: B. I. Publications Pvt. Ltd.Google Scholar
Masson-Delmotte, V (ed) (2018) Global Warming of 1.5oC: An IPCC Special Report on the Impacts of Global Warming of 1.5 C Above Pre-Industrial Levels and Related Global greenhouse Gas Emission Pathways, in the Context of Strengthening the Global Response to the Threat of Climate Change, Sustainable Development, and Efforts to Eradicate Poverty. Geneva: World Meteorological Organization.Google Scholar
Merow, C, Smith, MJ and Silander, J A (2013) A practical guide to MaxEnt for modeling species’ distributions: what it does, and why inputs and settings matter. Ecography 36, 10581069.CrossRefGoogle Scholar
Munoz, F, Estopinan, J, Bose, R, et al. (2021) Future impacts of climate change and deforestation on endemic trees of Western Ghats, South India. In On the Edge of Sixth Extinction in Biodiversity Hotspots: Facts, Needs, Solutions and Opportunities in Thailand and Adjacent Countries. Kolkata: CU Press.Google Scholar
Murugan, M, Shetty, PK, Anandhi, A, et al. (2009) Rainfall changes over tropical montane cloud forests of southern Western Ghats, India. Current Science 97, 17551760.Google Scholar
Nayar, BK and Geevarghese, KK (1993) Fern Flora of Malabar. New Delhi: Indus Publishing Company.Google Scholar
Omar, K and Elgamal, I (2021) IUCN red list and species distribution models as tools for the conservation of poorly known species: a case study of endemic plants Micromeria serbaliana and Veronica kaiseri in South Sinai, Egypt. Kew Bulletin 76, 477496.CrossRefGoogle Scholar
Palkar, RS, Janarthanam, MK and Sellappan, K (2020) Prediction of potential distribution and climatic factors influencing Garcinia indica in the Western Ghats of India using ecological niche modeling. National Academy Science Letters 43(6), 585591.CrossRefGoogle Scholar
Phillips, SJ, Anderson, RP, Dudík, M, et al. (2017) Opening the black box: an open-source release of MaxEnt. Ecography 40, 887893.CrossRefGoogle Scholar
Phillips, SJ, Anderson, RP and Schapire, RE (2006) Maximum entropy modeling of species geographic distributions. Ecological Modelling 190(3-4), 231259.CrossRefGoogle Scholar
Phillips, SJ and Dudik, M (2008) Modelling of species distributions with MaxEnt: new extensions and a comprehensive evaluation. Ecography 31, 161175.CrossRefGoogle Scholar
Potom, R and Nimasow, G (2019) Species distribution modeling of tea (Camellia sinensis) in Lohit district of Arunachal Pradesh, India. Int J Ecol Environ 45, 333344.Google Scholar
Pouteau, R, Meyer, JY, Blanchard, P, et al. (2016) Fern species richness and abundance are indicators of climate change on high-elevation islands: evidence from an elevational gradient on Tahiti (French Polynesia). Climatic Change 1, 143156.CrossRefGoogle Scholar
Pownitha, KV, Nagaraja, HPB, Charles, B, Vasudeva, R, Aravind, NA and Ravikanth, G (2022) Ecological niche modelling to identify suitable sites for cultivation of two important medicinal lianas of the Western Ghats, India. Tropical Ecology 63(3), 423432.Google Scholar
Qi, F, Wei, L, Yansui, L, et al. (2004) Impact of desertification and global warming on soil carbon in northern China. Journal of Geophysical Research, [Atmospheres] 109, D02104.Google Scholar
Raina, AP, Abraham, Z and Sivaraj, N (2015) Diversity analysis of Kaempferia galanga L. germplasm from South India using DIVA-GIS approach. Industrial Crops and Products 69, 433439.CrossRefGoogle Scholar
Ray, D, Behera, MD and Jacob, J (2014) Indian Brahmaputra valley offers significant potential for cultivation of rubber trees under changed climate. Current Science 10, 461469.Google Scholar
Roy, PS, Meiyappan, P, Joshi, PK, et al. (2016) Decadal land use and land cover classifications across India, 1985, 1995, 2005. Oak Ridge, Tennessee: ORNL DAAC.Google Scholar
Sarma, RR, Munsi, M and Ananthram, AN (2015) Effect of climate change on invasion risk of giant African snail (Achatina fulica Férussac, 1821: Achatinidae) in India. PLoS One 10, e0143724.CrossRefGoogle ScholarPubMed
Sen, S, Gode, A, Ramanujam, S, et al. (2016) Modeling the impact of climate change on wild Piper nigrum (Black Pepper) in Western Ghats, India using ecological niche models. J Plant Res 129, 10331040.CrossRefGoogle ScholarPubMed
Sharpe, JM (2019) Fern ecology and climate change. Indian Fern J 36, 179199.Google Scholar
Sharpe, JM, Mehltreter, K and Walker, LR (2010) Ecological Importance of Ferns. In Mehltreter, K, Walker, LR and Sharpe, JM (eds), Fern Ecology. Cambridge: Cambridge University Press.Google Scholar
Shrestha, N and Zhang, XC (2015) Is Huperzia hamiltonii (Spreng.) Trevis. a Himalayan endemic? An empirical evaluation using species distribution modeling. Indian Fern J 31, 154161.Google Scholar
Sony, RK, Sen, S, Kumar, S, et al. (2018) Niche models inform the effects of climate change on the endangered Nilgiri Tahr (Nilgiritragus hylocrius) populations in the southern Western Ghats, India. Ecological Engineering 1, 355363.CrossRefGoogle Scholar
Sreekumar, ER and Nameer, PO (2021) Impact of climate change on two high-altitude restricted and endemic flycatchers of the Western Ghats, India. Current Science 121, 1335.CrossRefGoogle Scholar
Sreekumar, ER and Nameer, PO (2022) A MaxEnt modelling approach to understand the climate change effects on the distributional range of White-bellied Sholakili Sholicola albiventris (Blanford, 1868) in the Western Ghats, India. Ecol 70, 101702.Google Scholar
Sreekumar, VB, Suganthasakthivel, R, Sreejith, KA, et al. (2016) Predictive distribution modelling of Calamus andamanicus Kurz, an Endemic Rattan from Andaman and Nicobar Islands, India. J For Environ Sci 32, 94–8.Google Scholar
Syfert, MM, Brummitt, NA, Coomes, DA, et al. (2018) Inferring diversity patterns along an elevation gradient from stacked SDMs: a case study on Mesoamerican ferns. Glob Ecol Conserv 16, e00433.Google Scholar
Thakur, KK, Bhat, P, Kumar, A, Ravikanth, G and Saikia, P (2022) Distribution mapping of Bauhinia vahlii Wight & Arn. in India using ecological niche modelling. Tropical Ecology 63(2), 286299.CrossRefGoogle Scholar
Walker, LR (1994) Effects of fern thickets on woodland development on landslides in Puerto Rico. Journal of Vegetation Science 5, 525532.CrossRefGoogle Scholar
Walker, LR, Mehltretter, K and Sharpe, JM (2010) Current and future directions in fern ecology. In Mehltretter, K Walker, LR and Sharpe, JM (eds), Fern Ecology. Cambridge: Cambridge University Press.Google Scholar
Walker, LR and Sharpe, JM (2010) Ferns, disturbance and succession. In Mehltretter, K Walker, LR and Sharpe, JM (eds), Fern Ecology. Cambridge: Cambridge University Press.Google Scholar
Wang, CJ, Wan, JZ, Zhang, ZX, et al. (2016) Identifying appropriate protected areas for endangered fern species under climate change. SpringerPlus 5, 112.Google ScholarPubMed
Wanga, WC, Lob, NJ, Changc, WI, et al. (2012) Modeling spatial distribution of a rare and endangered plant species (Brainea insignis) in central Taiwan. International archives of the photogrammetry, remote. Sensing and Spatial Information Sciences 39, 241246.Google Scholar
Williams, JN, Seo, C, Thorne, J, et al. (2009) Using species distribution models to predict new occurrences for rare plants. Diversity and Distributions 15, 565576.CrossRefGoogle Scholar
Yang, J, Huang, Y, Jiang, X, et al. (2022) Potential geographical distribution of the endangered plant Isoetes under human activities using MaxEnt and GARP. Global Ecology and Conservation 38, e02186.CrossRefGoogle Scholar
Zurell, D, Franklin, J, König, C, et al. (2020) A standard protocol for reporting species distribution models. Ecography 43, 12611277.CrossRefGoogle Scholar
Supplementary material: File

Thulasi et al. supplementary material

Thulasi et al. supplementary material
Download Thulasi et al. supplementary material(File)
File 12 KB