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Open AccessJournal ArticleDOI

Global potential distribution prediction of Xanthium italicum based on Maxent model.

Yang Zhang, +4 more
- 16 Aug 2021 - 
- Vol. 11, Iss: 1, pp 16545-16545
TLDR
In this paper, the Maxent model was used to predict current and future climatic conditions to estimate the potential global distribution of the invasive plant Xanthium italicum, and the prediction result of this model was excellent.
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.

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Citations
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Effects of climate change on the ecological niche of common hornbeam (Carpinus betulus L.)

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Multiple introductions and genetic admixture facilitate the successful invasion of Plantago virginica into China

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Predicting the distributions of Scleroderma guani (Hymenoptera: Bethylidae) under climate change in China

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References
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Journal ArticleDOI

Classification of Italian Xanthium strumarium complex based on biological traits, electrophoretic analysis and response to maize interference.

TL;DR: Xanthium strumarium complex was studied taking plant seeds from 16 diverse locations in Italy and a high correlation between seed reserve proteins and the genetic structure of this weed was also detected.
Journal ArticleDOI

Predictive Modeling of Suitable Habitats for Cinnamomum Camphora (L.) Presl Using Maxent Model under Climate Change in China.

TL;DR: It is found that accumulated temperature played a key role in the distribution of camphor trees and with the change of climate, the area of suitable range will increase and continue to move to the northwest of China.
Journal ArticleDOI

Predicting the Potential Geographic Distribution of Sirex nitobei in China under Climate Change Using Maximum Entropy Model

TL;DR: In this article, the authors used a maximum entropy model in conjunction with climate variables and shared socio-economic pathways to predict the current and future distribution of Sirex nitobei in China.
Journal ArticleDOI

Suitable habitat prediction of Sichuan snub-nosed monkeys ( Rhinopithecus roxellana ) and its implications for conservation in Baihe Nature Reserve, Sichuan, China

TL;DR: The findings highlighted that human activities in all three functional zones could be the most negative factor on suitable habitat distribution of Sichuan snub-nosed monkeys in the BNR.
Journal ArticleDOI

Predicting the current and future potential spatial distribution of endangered Rucervus eldii eldii (Sangai) using MaxEnt model

TL;DR: In this paper, the authors used MaxEnt to map and predict the current and future habitat suitability potential of Rucervus eldii eldii in Keibul Lamjao National Park (KLNP).
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