Maxent modeling for predicting the potential distribution of endangered medicinal plant (H. riparia Lour) in Yunnan, China

Yi, Yujun; Cheng, Xi; Zhang, Yang; Zhang, Shanghong

doi:10.1016/j.ecoleng.2016.04.010

Cited by 238 publications

(181 citation statements)

References 34 publications

Supporting

Mentioning

172

Contrasting

Unclassified

Order By: Relevance

“…For instance, Allen [70] found that increased global temperatures have negative influences on the distribution of woody plant species. Contrary to these studies, our study showed that climate warming would have positive effects on the suitable climatic habitat area of L. chinense, which was consistent with the study of the endangered medicinal plant (Homonoia riparia Lour) in Yunnan, China [46]. Compared to the belt distribution of the suitable climatic habitat gains of L. chinense, habitat losses were centrally distributed in an annular zone including Anhui and Jiangsu ( Figure S4), indicating a threat to the natural distribution of L. chinense and an urgent need for conservation.…”

Section: Discussionsupporting

confidence: 35%

“…We calculated the Table S3) and four topographical variables (the layers in Table S4), respectively [15]. We also calculated the Pearson correlation coefficient (r) by the "cor" command in R to assess the correlation among the 19 bioclimatic variables (the points in Table S5) and four topographical variables (the points in Table S6) of the 212 species' occurrence records, respectively [46]. Those 19 bioclimatic and four topographical variables were extracted from the corresponding layers using the "Extract Multi Values to Points" tool in ArcGIS 10.3.…”

Section: Correlation Analysis and Principal Component Analysismentioning

confidence: 99%

See 1 more Smart Citation

Effects of Climate Change on the Potentially Suitable Climatic Geographical Range of Liriodendron chinense

Zhang

Xie

et al. 2017

Forests

View full text Add to dashboard Cite

Abstract:Identifying the potentially suitable climatic geographical range for Liriodendron chinense (L. chinense) and predicting its responses to climate change is urgently necessary, as L. chinense is an important tertiary relict tree species. In this study, we simulated the potentially suitable climatic habitat of L. chinense in China using maximum entropy (MaxEnt) modeling. We found that the MaxEnt model was highly accurate with an average training Area Under the Curve (AUC) value of 0.912. Annual precipitation and mean temperature of the driest quarter are the main factors controlling the geographical distribution of L. chinense. Currently, the suitable climatic habitat of L. chinense is mainly located in Southeastern China. Forecasted patterns of predicted suitable climatic habitat show a significant change by the 2050s and 2070s, suggesting that the suitable climatic habitat of L. chinense would shift north with future climate change, based on four Representative Concentrations Pathways for carbon dioxide (CO 2 ) emissions. The southern extent of the current distribution would become unsuitable for L. chinense, pointing to a threat of extinction and highlighting the urgent need for conservation within the next half century. The potentially suitable climatic habitat of L. chinense was predicted to move further north, but those habitat gains may be inaccessible because of dispersal limitations. Our unique findings offer a climatic suitability map for L. chinense in China, which can help to identify locations where L. chinense may already exist, but has not yet been detected; to recognize locations where L. chinense is likely to spread in the future given forecasted climate change; and to select priority areas for its introduction, cultivation, and conservation.

show abstract

Section: Discussionsupporting

confidence: 35%

Section: Correlation Analysis and Principal Component Analysismentioning

confidence: 99%

Effects of Climate Change on the Potentially Suitable Climatic Geographical Range of Liriodendron chinense

Zhang

Xie

et al. 2017

Forests

View full text Add to dashboard Cite

show abstract

“…Esto permite considerar a dichos modelos como más precisos que un modelo obtenido al azar. Resultados similares en cuanto al desempeño de la AUC son reportados por diversos autores (Fielding and Bell, 1997;Rahim, 2016;Yi et al, 2016). Las variables bioclimáticas que aportaron más información al modelo de nicho potencial en el caso de Euptilotis neoxenus fueron la altitud, con 49% de contribución, y la temperatura mínima del mes más frío (Bio 6), con 22,3%, y la temperatura media anual (Bio 2) (rango de temperatura media mensual), con 11,5%.…”

Section: Modelado De Distribución Potencialunclassified

Factores biogeográficos y cambios de uso del suelo (2009-2013) en el nicho de "Trogon elegans ambiguus" y "Euptilotis neoxenus" en Chihuahua, México

Torres

Bravo-Peña

Alatorre-Cejudo

et al. 2018

CIG

View full text Add to dashboard Cite

Few studies have addressed the current state of the Trogon elegans ambiguus and Euptilotis neoxenus ecological niches, as well as the vegetation dynamics and land use changes where these birds live. This work estimates the potential distribution of Trogon elegans ambiguus and Euptilotis neoxenus in Chihuahua and studies the land use changes in two time periods (2009 and 2015). The MaxEnt software was used to model the ecological niches in Chihuahua, Mexico. The maps of changes in land use and plant cover were reclassified and the classes were homogenized. A crosstab analysis was used to compare correspondence matrices. The results indicate that Trogon elegans ambiguus and Euptilotis neoxenus underwent a niche loss in conifer and hardwood forests, which became farmland or pasture-bushes. Ecological niche modelling is a useful tool to identify suitable areas for species with NOM-059-SEMARNAT-2010 status. In the case of Trogon elegans ambiguus, land use changes mainly affect the municipalities of Temosachi and Madera.

show abstract

“…Moreover, after obtaining the absence data, the data was not reliable because the amount was limited. According to [16] in his observation, it showed that the use of Maxent model resulted stable and reliable prediction and surpass some other methods in the use of presence-only data.…”

Section: Introductionmentioning

confidence: 99%

“…The Maxent model is chosen because it offers several advantages such as: (1) it can use input presence-only data; (2) it can use input variable in the form of either continuous and categorical data; (3) it produces a stable and reliable prediction accuracy when the data condition is not complete and there is a few sample size; (4) it can directly produce a map of the suitability of spatial habitat explicitly; (5) and encompasses a jackknife test feature which can be used to evaluate environmental variable which is considered to be important [16].…”

Section: Introductionmentioning

confidence: 99%

Predicting the Spread of Acacia Nilotica Using Maximum Entropy Modeling

Dermawan¹,

Herdiyeni²,

Prasetyo³

et al. 2018

TELKOMNIKA

View full text Add to dashboard Cite

show abstract

Maxent modeling for predicting the potential distribution of endangered medicinal plant (H. riparia Lour) in Yunnan, China

Cited by 238 publications

References 34 publications

Effects of Climate Change on the Potentially Suitable Climatic Geographical Range of Liriodendron chinense

Effects of Climate Change on the Potentially Suitable Climatic Geographical Range of Liriodendron chinense

Factores biogeográficos y cambios de uso del suelo (2009-2013) en el nicho de "Trogon elegans ambiguus" y "Euptilotis neoxenus" en Chihuahua, México

Predicting the Spread of Acacia Nilotica Using Maximum Entropy Modeling

Contact Info

Product

Resources

About