Modeling the Current and Future Distribution of Indianthus virgatus (Roxb.) Suksathan & Borchs.: A Monotypic Plant Endemic to the Western Ghats‐Sri Lanka Biodiversity Hotspot

ABSTRACT Species distribution modeling (SDM) is an essential tool in ecology and conservation for predicting species distributions based on species presence/absence data and environmental variables. The present study aimed to understand the distribution pattern and habitat suitability of Indianthus...

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Published in:	Ecology and evolution Vol. 14; no. 10; pp. e70489 - n/a
Main Authors:	Vishnu, Shreekara Bhat, Pandi, Vivek, Madola, Indrakheela, Gopallawa, Bhathiya, Abraham, Gija Anna, Gayathri, Rajendiran, Yakandawala, Deepthi, Muthusamy, Annamalai
Format:	Journal Article
Language:	English
Published:	England John Wiley & Sons, Inc 01-10-2024 John Wiley and Sons Inc Wiley
Subjects:	Annual precipitation Applied Ecology Bioclimatology Biodiversity Biodiversity Ecology Biodiversity hot spots Biogeography Climate change Climate models Climate prediction conservation Conservation Ecology Distribution patterns Ecoinformatics Ecological models Endangered species Endemic plants Endemic species Field study Geographical distribution Global Change Ecology Habitat loss Habitats Indianthus virgatus IUCN MaxEnt modeling Precipitation Seasonal variations species distribution modeling Variables Wallace ecological modeling Sri Lanka India Wallace ecological modeling conservation MaxEnt modeling IUCN species distribution modeling climate change
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Summary:	ABSTRACT Species distribution modeling (SDM) is an essential tool in ecology and conservation for predicting species distributions based on species presence/absence data and environmental variables. The present study aimed to understand the distribution pattern and habitat suitability of Indianthus virgatus under current and future climate change scenarios (2050 and 2070) using MaxEnt (3.4.4) and Wallace Ecological Modeling (v2.1.2) tools. The study also intended to identify key environmental predictors of I. virgatus' distribution. Species occurrence data were collected from various sources, including herbarium (online and physical), field surveys, and online databases, yielding 105 unique locations in the Western Ghats (WG) of India and Sri Lanka. We used 19 bioclimatic variables and elevation data sourced from WorldClim for modeling. The MaxEnt and Wallace models showed excellent performance in predicting the distribution of I. virgatus, with area under the curve values of 0.958 (± 0.002) and 0.93, respectively. In MaxEnt modeling, Temperature Seasonality (bio4) was the most significant environmental parameter, followed by the Precipitation of the Coldest Quarter (bio19). In contrast, the Annual Mean Temperature (bio1), Temperature Seasonality (bio4), and Annual Precipitation (bio12) were among the key contributors in Wallace EcoMod. Both the models predicted relatively lesser areas in the species' distribution range as highly suitable habitats (HSH) in India and Sri Lanka. We found divergent trends in predicting I. virgatus distributions using MaxEnt and Wallace EcoMod, particularly for future projections. Nevertheless, both models predicted significant habitat loss under future climate change scenarios, especially under RCP85, with varying degrees of suitability across India and Sri Lanka. Overall, our findings on expected habitat loss under future climate change scenarios highlight the importance of conserving I. virgatus, which has already been declared critically endangered (CR) in Sri Lanka. This article projected the distribution of Indianthus virgatus, a monotypic plant endemic to the Western Ghats–Sri Lanka biodiversity hotspot. The article also highlights the role of environmental parameters in determining the current and future distribution projections using MaxEnt and Wallace EcoMod.
Bibliography:	The authors received no specific funding for this work. Funding ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23 Funding: The authors received no specific funding for this work.
ISSN:	2045-7758 2045-7758
DOI:	10.1002/ece3.70489