A machine learning approach targeting parameter estimation for plant functional type coexistence modeling using ELM-FATES (v2.0)

MLA

L. Li, et al. “A Machine Learning Approach Targeting Parameter Estimation for Plant Functional Type Coexistence Modeling Using ELM-FATES (v2.0).” Geoscientific Model Development, vol. 16, July 2023, pp. 4017–40. EBSCOhost, https://doi.org/10.5194/gmd-16-4017-2023.

APA

L. Li, Y. Fang, Z. Zheng, M. Shi, M. Longo, C. D. Koven, J. A. Holm, R. A. Fisher, N. G. McDowell, J. Chambers, & L. R. Leung. (2023). A machine learning approach targeting parameter estimation for plant functional type coexistence modeling using ELM-FATES (v2.0). Geoscientific Model Development, 16, 4017–4040. https://doi.org/10.5194/gmd-16-4017-2023

Chicago

L. Li, Y. Fang, Z. Zheng, M. Shi, M. Longo, C. D. Koven, J. A. Holm, et al. 2023. “A Machine Learning Approach Targeting Parameter Estimation for Plant Functional Type Coexistence Modeling Using ELM-FATES (v2.0).” Geoscientific Model Development 16 (July): 4017–40. doi:10.5194/gmd-16-4017-2023.