Bayesian Learning in a Nonlinear Multiscale State-Space Model

In many biological systems, the developmental processes of individuals play a crucial role in shaping the traits, characteristics, and growth patterns of subsequent generations. Throughout various stages of growth and maturation, organisms undergo significant changes that impact their overall fitness and reproductive success. These developmental stages, ranging from early cellular differentiation to reproductive maturity, each contribute uniquely to the organism's ability to survive and transmit biological information to offspring. Conversely, hereditary processes also influence the developmental stages of subsequent generations, creating a feedback loop where the heritable traits and adaptations of individuals as well as their health statuses such as disease resistance, metabolic efficiency, or physiological robustness can impact the developmental trajectories of future generations. This feedback loop between developmental processes and heredity continually shapes evolutionary trajectories, driving adaptation and resilience in populations over time.