Potential distributions of Sinopodophyllum hexandrum based on fuzzy matter element model

Abstract

Specific geographic spatial information about species is an important part of species conservation. This information is essential for addressing many challenges to species conservation such as those induced by climate change, as well as other ecological or biological factors. It is also important for both the domestication of a wild species.Sinopodophyllum hexandrum, a perennial herb in the berberidaceae family, is an endangered traditional Tibetan medical plant. The wild populations of this species are scarce, and its natural reproductive ability is weak. With an increase in popularity of this herb in both the domestic and international drug market, Sinopodophyllum hexandrum wild resources are being depleted, and traditional areas where the plant could be found no longer host this species. Without good knowledge about the habitat requirements of this species, species protection via habitat protection measures is not possible. Thus, the only viable strategy for protecting this species in the wild is to restrict sales of the plant when sourced from certain countries where the plant populations are known to be endangered. In addition to being essential for effective habitat protection, specific information about habitat requirements for Sinopodophyllum hexandrum also facilitate cultivating the plant more effectively鄄thus providing a sustainable supply for medical use. In our research, many samples of Sinopodophyllum http: / / www.ecologica.cn hexandrum were collected from 25 sampling sites. Based on Matter Element Mode theory, the relationships between plant yield and 12 climatic and environmental factors were established. Using these data as a base, we calculated the optimum habitat conditions for Sinopodophyllum hexandrum. The next step was to use the maximum entropy model to determine the relative importance of each environmental factor, and thus determine the most limiting habitat criteria. Finally, the probable spatial distribution of Sinopodophyllum hexandrum across seven provinces in western China was determined based on the weighted average method and GIS spatial analysis of habitat conditions. The root鄄mean鄄square error ( RMSE) was used to evaluate the accuracy of the model忆s prediction.The RMSE value reached 8.6%: a value which indicates predictive accuracy of the model to have reached the level of " Excellent 冶 . The results show five dominant climatic factors controlling Sinopodophyllum hexandrum distribution. These five dominant features are 1 ) minimum temperature of coldest month (TMIN) , 2 ) annual mean temperature ( AMT ) , 3 ) maximum temperature of warmest month ( TMAX ) , 4 ) Annual sunshine hours ( ASH) and 5) elevation above sea level ( ASL) . The percentage of unsuitable habitat for Sinopodophyllum hexandrum in this area was 61.76%, with 20.11% classified as marginally suitable habitat, 7.70% classified as moderately suitable habitat, and 10. 43% highly suitable habitat. Thus the growing area for Sinopodophyllum hexandrum, whether natural or cultivated, is limited. Our results showed that mod...

Optimization of the Fuzzy Matter Element Method for Predicting Species Suitability Distribution Based on Environmental Data

“…For the detection of marginal peripheral populations, provenance distribution modelling may represent a valuable step forward in spatial analysis [10]. To improve the accuracy of the model and deal with the uncertainty, [22] Scutellaria baicalensis Georgi 15 baicalin The whole of China [23] Cornus officinalis 21 loganin Qinling region [24] Sinopodophyllum hexandrum (Royle) Ying 12 fruit yield 7 provinces in western [25] Angelica sinensis (Oliv.) Diels 14 ferulic acid 10 provinces in western [26] Schisandra chinensis (Turcz.)…”