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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 Open the ORCID record for R. Thulasi [Opens in a new window] ,
Francois Munoz Open the ORCID record for Francois Munoz [Opens in a new window] ,
E.R. Sreekumar Open the ORCID record for E.R. Sreekumar [Opens in a new window] ,
Maya C. Nair Open the ORCID record for Maya C. Nair [Opens in a new window]  and
K.P. Rajesh Open the ORCID record for K.P. Rajesh [Opens in a new window]
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]
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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.

Keywords

Dryopteridaceaeecological niche modelling (ENM)species distribution modelling (SDM)MaxEnt softwareQ-GIS
Type
Research Article
Information
Journal of Tropical Ecology , Volume 40 , 2024 , e24
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© The Author(s), 2024. Published by Cambridge University Press

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