ArticleScientific reports2020
Adaptive fitness of Sapindus emarginatus Vahl populations towards future climatic regimes and the limiting factors of its distribution.
Article in Scientific reports, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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3 citing papers in PubMed, 8 citations in OpenAlex.
- Modeling habitat suitability of bats to identify high priority areas for field monitoring and conservation.Environmental science and pollution research international · 2022Article
- Predicting the potential global distribution of Sapindus mukorossi under climate change based on MaxEnt modelling.Environmental science and pollution research international · 2022Article
- EST-SSR-based landscape genetics ofEcology and evolution · 2021Article
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Authors and funding
5 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Sapindus emarginatus Vahl (Sapindaceae) also known as 'Indian Soap nut' is significantly important for saponin content in its fruits. However, its current population in India is heavily fragmented due to a lack of sustainable harvesting practices. Moreover, changing climatic regimes may further limit its distribution and possibly compromise the survival of the species in nature. The aim of the present study was to: predict the future distribution range of S. emarginatus; identify the bioclimatic variables limiting this distribution and to evaluate its adaptive fitness and genomic resilience towards these variables. To determine future species distribution range and identify limiting bioclimatic variables, we applied two different ecological niche models (ENMs; BioClim and MaxEnt) on real occurrence data (n = 88 locations). The adaptive fitness of the species was evaluated by quantifying the genetic variability with AFLP markers and marker-environmental associations, using AFLP-associated Bayesian statistics. We found 77% overlap between the baseline (2030) and predicted (2100) species distribution ranges, which were primarily determined by maximum temperature (T
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