Predicting the potential geographical distribution of Ageratina adenophora in China using equilibrium occurrence data and ensemble model

Abstract

Invasive alien plants (IAPs) pose a significant threat to the ecological environment and agricultural production in China. Ageratina adenophora is one of the most aggressive IAPs in China and poses serious ecological and socioeconomic threats. Estimating the distribution pattern of A. adenophora in China can provide baseline data for preventing damage by this weed. In the present study, based on the equilibrium occurrence data of A. adenophora in China and related environmental variables, we used an ensemble model to predict the distribution pattern of A. adenophora in China under climate change. Our findings indicated that true skill statistic (TSS), area under the receiver operating characteristic (ROC) curve (AUC), and Cohen’s Kappa (KAPPA) values for the ensemble model were 0.925, 0.993, and 0.936, respectively. The prediction results of the ensemble model were more accurate than those of the single models. Temperature variables had a significant impact on the potential geographical distribution (PGD) of A. adenophora in China. The total, high, and moderate suitability habitat areas of A. adenophora in China were 153.82 × 104, 92.13 × 104, and 21.04 × 104 km2, respectively, accounting for 16.02, 9.60, and 2.19% of the Chinese mainland area, respectively. The PGD of A. adenophora in China under the current climate is mainly located in southwestern and southeastern China, which are located in the tropical and subtropical zone. The high-suitability habitat areas of A. adenophora decreased under the future climate scenarios, mainly by changing to moderately suitable habitats in Southwest China. The geographical distribution of A. adenophora in southwestern China is currently saturated and will spread to southeastern China under climate change in the future. More attention should be paid to early warning and monitoring of A. adenophora in southeastern China to prevent its further spread.

Geographical Distribution Pattern and Ecological Niche of Solenopsis invicta Buren in China under Climate Change

“…As the geographical distribution of highly potential suitable areas of S. invicta is irregular and it is difficult to describe its migration tracks, we used the potential highly suitable area centroids to describe the migration tracks of S. invicta in China [38]. The centroids of highly suitable areas of S. invicta under current and future climatic conditions were obtained using the Feature to Point function of ArcGIS software.…”

Assessing risk from invasive alien plants in China: Reconstructing invasion history and estimating distribution patterns of Lolium temulentum and Aegilops tauschii

“…MaxEnt uses presence data alone, and provides efficient algorithms with optimal performance, toilless analysis, and avoids overfitting on other SDMs ( Elith et al., 2006 ; Phillips et al., 2006 ; Phillips and Dudík, 2008 ). Previous studies on IAPs, including Prosopis juliflora , Ageratina adenophora , and Cenchrus spinifex , used the MaxEnt model to predict geographical distribution patterns ( Cao et al., 2021 ; Singh et al., 2021 ; Xian et al., 2022 ). However, the default MaxEnt model has some methodological issues in balancing goodness-of-fit with model complexity, which leads to overfitting and poor transferability when projected in a novel environment ( Warren and Seifert, 2011 ; Guevara et al., 2018 ).…”