Global potential distribution prediction of Xanthium italicum based on Maxent model

Abstract Alien invasive plants pose a threat to global biodiversity and the cost of control continues to rise. Early detection and prediction of potential risk areas are essential to minimize ecological and socio-economic costs. In this study, the Maxent model was used to predict current and future...

Descripción completa

Guardado en:

Detalles Bibliográficos
Autores principales:	Yang Zhang, Jieshi Tang, Gang Ren, Kaixin Zhao, Xianfang Wang
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2021
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/746a1266e9da4b9b8354012fc10a394b
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

id	oai:doaj.org-article:746a1266e9da4b9b8354012fc10a394b
record_format	dspace
spelling	oai:doaj.org-article:746a1266e9da4b9b8354012fc10a394b2021-12-02T15:10:34ZGlobal potential distribution prediction of Xanthium italicum based on Maxent model10.1038/s41598-021-96041-z2045-2322https://doaj.org/article/746a1266e9da4b9b8354012fc10a394b2021-08-01T00:00:00Zhttps://doi.org/10.1038/s41598-021-96041-zhttps://doaj.org/toc/2045-2322Abstract Alien invasive plants pose a threat to global biodiversity and the cost of control continues to rise. Early detection and prediction of potential risk areas are essential to minimize ecological and socio-economic costs. In this study, the Maxent model was used to predict current and future climatic conditions to estimate the potential global distribution of the invasive plant Xanthium italicum. The model consists of 366 occurrence records (10 repeats, 75% for calibration and 25% for verification) and 10 climate prediction variables. According to the model forecast, the distribution of X. italicum was expected to shrink in future climate scenarios with human intervention, which may be mainly caused by the rise in global average annual temperature. The ROC curve showed that the AUC values of the training set and the test set are 0.965 and 0.906, respectively, indicating that the prediction result of this model was excellent. The contribution rates of annual mean temperature, monthly mean diurnal temperature range, standard deviation of temperature seasonal change and annual average precipitation to the geographical distribution of X. italicum were 65.3%, 11.2%, 9.0%, and 7.7%, respectively, and the total contribution rate was 93.2%. These four variables are the dominant environmental factors affecting the potential distribution of X. italicum, and the influence of temperature is greater than that of precipitation. Through our study on the potential distribution prediction of X. italicum under the future climatic conditions, it has contribution for all countries to strengthen its monitoring, prevention and control, including early warning.Yang ZhangJieshi TangGang RenKaixin ZhaoXianfang WangNature PortfolioarticleMedicineRScienceQENScientific Reports, Vol 11, Iss 1, Pp 1-10 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Yang Zhang Jieshi Tang Gang Ren Kaixin Zhao Xianfang Wang Global potential distribution prediction of Xanthium italicum based on Maxent model
description	Abstract Alien invasive plants pose a threat to global biodiversity and the cost of control continues to rise. Early detection and prediction of potential risk areas are essential to minimize ecological and socio-economic costs. In this study, the Maxent model was used to predict current and future climatic conditions to estimate the potential global distribution of the invasive plant Xanthium italicum. The model consists of 366 occurrence records (10 repeats, 75% for calibration and 25% for verification) and 10 climate prediction variables. According to the model forecast, the distribution of X. italicum was expected to shrink in future climate scenarios with human intervention, which may be mainly caused by the rise in global average annual temperature. The ROC curve showed that the AUC values of the training set and the test set are 0.965 and 0.906, respectively, indicating that the prediction result of this model was excellent. The contribution rates of annual mean temperature, monthly mean diurnal temperature range, standard deviation of temperature seasonal change and annual average precipitation to the geographical distribution of X. italicum were 65.3%, 11.2%, 9.0%, and 7.7%, respectively, and the total contribution rate was 93.2%. These four variables are the dominant environmental factors affecting the potential distribution of X. italicum, and the influence of temperature is greater than that of precipitation. Through our study on the potential distribution prediction of X. italicum under the future climatic conditions, it has contribution for all countries to strengthen its monitoring, prevention and control, including early warning.
format	article
author	Yang Zhang Jieshi Tang Gang Ren Kaixin Zhao Xianfang Wang
author_facet	Yang Zhang Jieshi Tang Gang Ren Kaixin Zhao Xianfang Wang
author_sort	Yang Zhang
title	Global potential distribution prediction of Xanthium italicum based on Maxent model
title_short	Global potential distribution prediction of Xanthium italicum based on Maxent model
title_full	Global potential distribution prediction of Xanthium italicum based on Maxent model
title_fullStr	Global potential distribution prediction of Xanthium italicum based on Maxent model
title_full_unstemmed	Global potential distribution prediction of Xanthium italicum based on Maxent model
title_sort	global potential distribution prediction of xanthium italicum based on maxent model
publisher	Nature Portfolio
publishDate	2021
url	https://doaj.org/article/746a1266e9da4b9b8354012fc10a394b
work_keys_str_mv	AT yangzhang globalpotentialdistributionpredictionofxanthiumitalicumbasedonmaxentmodel AT jieshitang globalpotentialdistributionpredictionofxanthiumitalicumbasedonmaxentmodel AT gangren globalpotentialdistributionpredictionofxanthiumitalicumbasedonmaxentmodel AT kaixinzhao globalpotentialdistributionpredictionofxanthiumitalicumbasedonmaxentmodel AT xianfangwang globalpotentialdistributionpredictionofxanthiumitalicumbasedonmaxentmodel
_version_	1718387697467260928

Global potential distribution prediction of Xanthium italicum based on Maxent model

Ejemplares similares