Ahmadi, M., Hemami, M. R., Kaboli, M. and Shabani, F. (2023). MaxEnt brings comparable results when the input data are being completed; Model parameterization of four species distribution models. Ecol. Evol. 13: doi:10.1002/ece3.9827.
Borotová, P., Galovičová, L., Vukovic, N. L., Vukic, M., Kunová, S., Hanus, P., Kowalczewski, P., Bakay, L. and Kačániová, M. (2022). Role of Litsea cubeba essential oil in agricultural products safety: antioxidant and antimicrobial applications. Plants (Basel) 11: doi:10.3390/plants11111504.
Elith, J., Phillips, S. J., Hastie, T., Dudík, M., Chee, Y. E. and Yates, C. J. (2011). A statistical explanation of MaxEnt for ecologists. Divers. Distrib. 17: 43-57. doi:10.1111/j.1472-4642.2010.00725.x.
Kamle, M., Mahato, D. K., Lee, K. E., Bajpai, V. K., Gajurel, P. R., Gu, K. S. and Kumar, P. (2019). Ethnopharmacological properties and medicinal uses of Litsea cubeba. Plants (Basel) 8: doi:10.3390/plants8060150.
Matsane, W., Dhau, I., Mothapo, M. C. and Thamaga, K. H. (2025). Modelling the potential distribution of african wormwood (Artemisia afra) using a machine learning algorithm-based approach (MaxEnt) in Sekhukhune district, South Africa. Ecol. Evol. 15: doi:10.1002/ece3.71866.
Shan, Y., Shen, H., Huang, L., Hamezah, H. S., Han, R., Ren, X., Zhang, C. and Tong, X. (2025). Optimized MaxEnt analysis revealing the change of potential distribution area of Lygodium japonicum in China driven by global warming. Front. Plant Sci. 16: doi:10.3389/fpls.2025.1601956.
Su, Q., Du, Z., Luo, Y., Zhou, B., Xiao, Y. and Zou, Z. (2024). MaxEnt Modeling for predicting the potential geographical distribution of Hydrocera triflora since the last interglacial and under future climate scenarios. Biology (Basel) 13: doi:10.3390/biology13090745.
Tesfamariam, B. G., Gessesse, B. and Melgani, F. (2022). MaxEnt-based modeling of suitable habitat for rehabilitation of Podocarpus forest at landscape-scale. Environ. Syst. Res. 11: doi:10.1186/s40068-022-00248-6.
Wang, M. and Guan, Q. (2023). Prediction of potential suitable areas for Broussonetia papyrifera in China using the MaxEnt model and CIMP6 data. J. Plant Ecol. 16: doi:10.1093/jpe/rtad006.
Wang, X., Ning, X., Liao, G., Fan, G., Shi, X., Fu, D., Wang, Z., Chen, S. and Wang, J. (2023). Phenotypic diversity of Litsea cubeba in Jiangxi China and the identification of germplasms with desirable characteristics. Forests 14: doi:10.3390/f14122283.
Wang, Y., Ren, X., Wang, K., Lin, W., Wang, P., Liu, Z., Zhang, H. and Zhou, N. (2025). Maxent model-based prediction of the potential distribution of Fritillaria taipaiensis P. Y. Li. Sci. Rep. 15: doi:10.1038/s41598-025-01682-z.
Xie, M., Song, X., Zhang, X., Ma, Y., Song, Z., Li, F., Li, W., Fan, L. and Ma, H. (2025). Suitability mapping of native tree species in dry-hot valleys of Yunnan based on InVEST-MaxEnt coupled modeling: model validation framework with native tree species actual distribution and seed germination. Front. Plant Sci. 16: doi:10.3389/fpls.2025.1577623.
Yahaya, I. I., Wang, C., Ogbue, C. P. and Yahaya, M. S. (2025). Remote sensing and MaxEnt modeling of canopy and non-canopy forest tree species in Taraba State for biodiversity conservation and ecosystem management. Front. For. Glob. Change 8: doi:10.3389/ffgc.2025.1631859.
Zhou, Y., Zhang, Z., Zhu, B., Cheng, X., Yang, L., Gao, M. and Kong, R. (2021). MaxEnt modeling based on CMIP6 models to project potential suitable zones for Cunninghamia lanceolata in China. Forests 12: doi:10.3390/f12060752.
Borotová, P., Galovičová, L., Vukovic, N. L., Vukic, M., Kunová, S., Hanus, P., Kowalczewski, P., Bakay, L. and Kačániová, M. (2022). Role of Litsea cubeba essential oil in agricultural products safety: antioxidant and antimicrobial applications. Plants (Basel) 11: doi:10.3390/plants11111504.
Elith, J., Phillips, S. J., Hastie, T., Dudík, M., Chee, Y. E. and Yates, C. J. (2011). A statistical explanation of MaxEnt for ecologists. Divers. Distrib. 17: 43-57. doi:10.1111/j.1472-4642.2010.00725.x.
Kamle, M., Mahato, D. K., Lee, K. E., Bajpai, V. K., Gajurel, P. R., Gu, K. S. and Kumar, P. (2019). Ethnopharmacological properties and medicinal uses of Litsea cubeba. Plants (Basel) 8: doi:10.3390/plants8060150.
Matsane, W., Dhau, I., Mothapo, M. C. and Thamaga, K. H. (2025). Modelling the potential distribution of african wormwood (Artemisia afra) using a machine learning algorithm-based approach (MaxEnt) in Sekhukhune district, South Africa. Ecol. Evol. 15: doi:10.1002/ece3.71866.
Shan, Y., Shen, H., Huang, L., Hamezah, H. S., Han, R., Ren, X., Zhang, C. and Tong, X. (2025). Optimized MaxEnt analysis revealing the change of potential distribution area of Lygodium japonicum in China driven by global warming. Front. Plant Sci. 16: doi:10.3389/fpls.2025.1601956.
Su, Q., Du, Z., Luo, Y., Zhou, B., Xiao, Y. and Zou, Z. (2024). MaxEnt Modeling for predicting the potential geographical distribution of Hydrocera triflora since the last interglacial and under future climate scenarios. Biology (Basel) 13: doi:10.3390/biology13090745.
Tesfamariam, B. G., Gessesse, B. and Melgani, F. (2022). MaxEnt-based modeling of suitable habitat for rehabilitation of Podocarpus forest at landscape-scale. Environ. Syst. Res. 11: doi:10.1186/s40068-022-00248-6.
Wang, M. and Guan, Q. (2023). Prediction of potential suitable areas for Broussonetia papyrifera in China using the MaxEnt model and CIMP6 data. J. Plant Ecol. 16: doi:10.1093/jpe/rtad006.
Wang, X., Ning, X., Liao, G., Fan, G., Shi, X., Fu, D., Wang, Z., Chen, S. and Wang, J. (2023). Phenotypic diversity of Litsea cubeba in Jiangxi China and the identification of germplasms with desirable characteristics. Forests 14: doi:10.3390/f14122283.
Wang, Y., Ren, X., Wang, K., Lin, W., Wang, P., Liu, Z., Zhang, H. and Zhou, N. (2025). Maxent model-based prediction of the potential distribution of Fritillaria taipaiensis P. Y. Li. Sci. Rep. 15: doi:10.1038/s41598-025-01682-z.
Xie, M., Song, X., Zhang, X., Ma, Y., Song, Z., Li, F., Li, W., Fan, L. and Ma, H. (2025). Suitability mapping of native tree species in dry-hot valleys of Yunnan based on InVEST-MaxEnt coupled modeling: model validation framework with native tree species actual distribution and seed germination. Front. Plant Sci. 16: doi:10.3389/fpls.2025.1577623.
Yahaya, I. I., Wang, C., Ogbue, C. P. and Yahaya, M. S. (2025). Remote sensing and MaxEnt modeling of canopy and non-canopy forest tree species in Taraba State for biodiversity conservation and ecosystem management. Front. For. Glob. Change 8: doi:10.3389/ffgc.2025.1631859.
Zhou, Y., Zhang, Z., Zhu, B., Cheng, X., Yang, L., Gao, M. and Kong, R. (2021). MaxEnt modeling based on CMIP6 models to project potential suitable zones for Cunninghamia lanceolata in China. Forests 12: doi:10.3390/f12060752.










