Survival Analysis of Tree Species: Investigating Mycorrhizal Types, Soil Characteristics, and Environmental Factors.
Presentation Type
Poster
Student
Yes
Track
Other
Abstract
Plant survival is a pivotal factor influencing forest dynamics, with survival probabilities contingent on various factors, including mycorrhizal associations, soil characteristics, and environmental conditions. While existing literature has predominantly utilized descriptive analysis for tree survival, our research delves into the intriguing exploration of how different survival models fit the data.
This study (based on secondary data) employs a factorial blocked design field experiment, monitoring 3,024 seedlings across four tree species, seven soil sources, and varying light levels. The comprehensive dataset derived from this experiment is analyzed, revealing distinct survival rates among tree species.
In our research, we employed diverse survival models to examine tree species' survival rates. Utilizing a backward elimination technique, we identified the most significant regressors. Subsequently, various survival models were applied to determine the optimal model that best characterizes the data. Evaluation of multiple survival models, including Weibull, Lognormal, and Exponential, indicates that the Weibull model outperforms others. It is evidenced by the model's lowest AIC, AICC, and BIC values, signifying superior goodness of fit. Finally, the COX-PH model was employed for further refinement and fitting of the overall model.
Keywords: Survival Analysis, Weibull model, Mycorrhizal types, Soil characteristics, Environmental factors, Forest management, COX-PH model.
Start Date
2-6-2024 1:00 PM
End Date
2-6-2024 2:00 PM
Survival Analysis of Tree Species: Investigating Mycorrhizal Types, Soil Characteristics, and Environmental Factors.
Volstorff A
Plant survival is a pivotal factor influencing forest dynamics, with survival probabilities contingent on various factors, including mycorrhizal associations, soil characteristics, and environmental conditions. While existing literature has predominantly utilized descriptive analysis for tree survival, our research delves into the intriguing exploration of how different survival models fit the data.
This study (based on secondary data) employs a factorial blocked design field experiment, monitoring 3,024 seedlings across four tree species, seven soil sources, and varying light levels. The comprehensive dataset derived from this experiment is analyzed, revealing distinct survival rates among tree species.
In our research, we employed diverse survival models to examine tree species' survival rates. Utilizing a backward elimination technique, we identified the most significant regressors. Subsequently, various survival models were applied to determine the optimal model that best characterizes the data. Evaluation of multiple survival models, including Weibull, Lognormal, and Exponential, indicates that the Weibull model outperforms others. It is evidenced by the model's lowest AIC, AICC, and BIC values, signifying superior goodness of fit. Finally, the COX-PH model was employed for further refinement and fitting of the overall model.
Keywords: Survival Analysis, Weibull model, Mycorrhizal types, Soil characteristics, Environmental factors, Forest management, COX-PH model.