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Ensemble species distribution model of threatened Cycas circinalis and Cycas nathorstii in Kannur district, Kerala, India
Journal Article
đź“–
Manjusha K, Jeevan K, George S, Nawab NP, Muthukumar A, Magesh CR, Muthuchamy M. 2025. Ensemble species distribution model of threatened Cycas circinalis and Cycas nathorstii in Kannur district, Kerala, India. Plant Ecology 226
(4): 389-407.
https://doi.org/10.1007/s11258-025-01502-4.
Abstract
The impact of climate change on the distribution of species of the single cycad genus Cycas L. of the family Cycadaceae in Kerala can be assessed by forecasting the habitat suitability of these species. It will aid in conservation efforts as they are endangered. The current study aimed to predict the current, future and paleoclimatic distribution of potentially suitable habitats of Cycas circinalis and Cycas nathorstii in Kannur district, Kerala. Ensemble function in “sdm” package used to integrate the five modeling algorithms, namely Generalized Linear Model (GLM), Generalized Additive Model (GAM), Random Forest (RF), Boosted Regression Tree (BRT), and Maximum Entropy (MaxEnt) as the models are effective and flexible at small sample size. Annual mean precipitation was the prime contributing factor for the current suitability model of both species, followed by yearly mean temperature. In the Kannur district, C. circinalis showed not suitable, least suitable, and moderately suitable areas, and C. nathorstii exhibited the least suitable, moderately suitable, suitable and highly suitable regions during the current scenario. The distribution model of C. circinalis to future SSP 245 and SSP 585 scenarios showed a minor increase in suitability during 2021–2040, 2041–2060, 2061–2080 and 2081–2100 for Kannur district and Kerala. Likewise, C. nathorstii exhibits a suitability area increase in all four time periods. The niche breadth metric resulted in habitat specificity, but at a low rate for both species and exhibited niche overlap among them. The study will encourage exploring the new populations in the area based on the model and to progress conservation efforts.
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