Replication Data for: Predicting the impact of climate change on the distribution of two threatened Himalayan medicinal plants of Liliaceae in Nepal
<|begin_of_text|><|start_header_id|>system<|end_header_id|> You are a research archivist expert in dataset metadata. Answer the question truthfully.  <|eot_id|><|start_header_id|>user<|end_header_id|> Here is the Description of a dataset. Description:'Predicting the potential distribution of medicinal plants in response to climate change isessential for their conservation and management. Contributing to the management program, this study aimed to predict the distribution of two threatened medicinal plants, Fritillaria cirrhosa and Lilium nepalense. The location of focal species gathered from herbarium specimen housed in different herbaria and online databases were geo-referenced and checked for spatial autocorrelation. The predictive environmental variables were selected, and MaxEnt software was used to model the current and future distributions of focal species. Four Representative Concentration Pathway (RCP) trajectories of the BCC-CSM1.1 model were used as the future (2050) projection layer. The MaxEnt modelling delineated the potential distribution of F. cirrhosa and L. nepalen' . Please return only a json list of at most 3 Keywords corresponding to the Description:.<|eot_id|><|start_header_id|>assistant<|end_header_id|> {"Answer" : ["Commercial exploitation","Conservation","Fritillaria cirrhosa","Lilium nepalense","Lily","MaxEnt modelling","Species distribution"]} <|eot_id|>
 Here is the Description of a dataset. Description:'Predicting the potential distribution of medicinal plants in response to climate change isessential for their conservation and management. Contributing to the management program, this study aimed to predict the distribution of two threatened medicinal plants, Fritillaria cirrhosa and Lilium nepalense. The location of focal species gathered from herbarium specimen housed in different herbaria and online databases were geo-referenced and checked for spatial autocorrelation. The predictive environmental variables were selected, and MaxEnt software was used to model the current and future distributions of focal species. Four Representative Concentration Pathway (RCP) trajectories of the BCC-CSM1.1 model were used as the future (2050) projection layer. The MaxEnt modelling delineated the potential distribution of F. cirrhosa and L. nepalen' . Please return only a json list of at most 3 Keywords corresponding to the Description:.
Predicting the potential distribution of medicinal plants in response to climate change isessential for their conservation and management. Contributing to the management program, this study aimed to predict the distribution of two threatened medicinal plants, Fritillaria cirrhosa and Lilium nepalense. The location of focal species gathered from herbarium specimen housed in different herbaria and online databases were geo-referenced and checked for spatial autocorrelation. The predictive environmental variables were selected, and MaxEnt software was used to model the current and future distributions of focal species. Four Representative Concentration Pathway (RCP) trajectories of the BCC-CSM1.1 model were used as the future (2050) projection layer. The MaxEnt modelling delineated the potential distribution of F. cirrhosa and L. nepalen
Commercial exploitation; Conservation; Fritillaria cirrhosa; Lilium nepalense; Lily; MaxEnt modelling; Species distribution