Study on Lamprey Population Growth and Sex Differentiation Models Using Bayesian Methods
DOI:
https://doi.org/10.54097/q87v5175Keywords:
Logistic Growth Model, Bayesian Estimation, Bayesian Network Inference, Markov Chain Monte Carlo simulation.Abstract
This study developed a predictive model to assess the ecological impacts of changing sex ratios in various lamprey populations, categorizing them into parasitic, non-parasitic, anadromous, and potamodromous types. Critical data on temperature tolerance and growth durations for four representative species were collected to analyze the interactions under different sex ratios, focusing on both competitive and mutualistic dynamics within communities. The model explored sex differentiation mechanisms through various adjustment modes, linking lamprey growth rates to environmental factors like temperature and resource availability. Bayesian methods were utilized to integrate prior knowledge and address uncertainties, predicting larvae's sex-based outcomes. Additionally, a Bayesian biomass dynamic model evaluated population dynamics considering birth and death rates. Markov Chain Monte Carlo (MCMC) simulations within this Bayesian framework facilitated robust parameter estimation, significantly enhancing the understanding of how sex ratio changes impact species-specific and regional biodiversity and population dynamics.
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