Fibraurea tinctoria Lour. (Menispermaceae family) is an original plant in China, Indonesia, Malaysia, Thailand, and Vietnam (Wu et al. 1962). F. tinctoria is a perennial yellow woody climber which can climb up to 40m long with a stem diameter of 5 cm and is often distributed in lowland forests with an elevation less than 1200m (Al-Saikhan 2020). The species has been widely used in traditional medicines (Perry and Metzger 1980; Niwat et al. 2005). Its stem bark is utilized to cure wounds and inflammation (Al-Saikhan 2020), food poisoning and paralyze, dysentery, analgesic, antipyretic, antidote (Galappathie et al. 2014), diarrhea, and hepatitis (Niwat et al. 2005). In Vietnam, F. tinctoria is distributed in secondary forests from the northern mountainous provinces to the Central provinces with elevations less than 1,000m above sea level. In the past, F. tinctoria has large populations in the natural forest but is considered as a by-product of forest products and less paid attention. Hence, overexploitation for a long time led to the dramatic decline of the species (Pham and Nguyen 2015). This plant has been listed in the Red Book of Vietnam since 1996 (Ministry of Environmental Science and Technology, 1996), and belongs to group IIA which needs to be protected (Decree 06/2019/ND-CP).
Strategic science and technology research programs to develop the pharmaceutical chemical industry to the year 2020 in Vietnam clearly stated the goal to study and develop the raw material area of F. tinctoria to extract 1,000kg palmatine hydrochloride/year (Decision Decree No. 61/2007/QD/TTg). Recently, F. tinctoria has been experimented and planted successfully in many places (Vu et al. 2017; Pham, 2014), however, whether the plants meet the relevant chemical composition standards has not been paid attention which can reduce cultivation efficiency and waste of human and material resources. Moreover, the quality of chemical metabolites in herbs is influenced by a multitude of factors, such as the germplasm, plant collection time, and environmental factors. Above all, research has demonstrated that variation in the quality of medical plants is mainly due to environmental factors (Guo et al. 2013; Ncube et al. 2012).
Ecological niche models (ENM) are statistically robust representations that have been widely used for many years to estimate the potential geographic distribution of any species by using (i) known geographical occurrences and (ii) projected environmental factors (Guisan and Zimmermann, 2000; Pearson, 2010). These models simply employ the relationship between the two aforementioned components to determine the suitable habitats where the populations of that particular species can thrive (Almadrones-Reyes and Dagamac 2018). Hence, such models have been used as a promising tool for conservation and understanding species persistence especially to localities whose records are considered limited (Lu et al. 2012; Peterson 2006, Phillips et al. 2004). With fewer data requirements, single algorithms for species distribution are preferred to be employed effectively (Kaky et al. 2020) for poorly studied taxa (Kearney and Porter, 2009) or data-poor regions (Truong et al. 2017). Such regression or correlational algorithms has been used widely in predicting the potential geographical distribution of many species including those plant species that have important medicinal values like Justicia sp. (Yang et al. 2013), Rosa sp. (Abdelaal et al. 2019), Carthamus sp. (Wei et al. 2018), etc.
To assess the correlation between medicinal components with environmental factors, linear regression analysis using Ordinary Least Square (OLS) method has been used in some studies (e.g. Xu et al. 2020; Yuan et al. 2020). However, in fact, real data, especially ecological data often exhibit spatial patterns (Beale et al. 2010; Ver Hoef et al. 2018). Hence, without considering the spatial autocorrelation, this non-spatial regression method can lead to low precision and high error rates (Beale et al. 2010). Spatial autoregessive (SAR) model is specifically designed to model spatially autocorrelated data based on neighborhood relationships which can improve the performance of spatial data (Beale et al. 2010; Pace and Gilley 1997; Ver Hoef et al. 2018).
Intending to develop medicinal plant cultivation for conservation and to improve the quality of traditional medicine in Vietnam, this study, therefore, aimed to (i) determine ecological factors affecting the distribution of F. tinctoria and accumulation of palmatine content in F. tinctoria and (ii) identify suitable areas in Vietnam where F. tinctoria can be successfully cultivated. To achieve these objectives, the study built an environmental suitability map of the habitat for F. tinctoria based on the Maxent and SAR model to assess the correlation between the chemical content and environmental variables. Finally, the predicted areas with suitable environments for the cultivation of F. tinctoria with high content of palmatine were identified.