In mark-recapture studies, survival parameters are often subject to individual heterogeneity and affected by environmental effects and observation errors. Besides that, recent interest has included additional complexities such as individual covariance and random effects within the statistical framework. To meet the requirements of analysing complex mark-recapture or mark-recapture-recovery data, novel Bayesian fitting state-space models provide a practical tool by coupling a model of mechanistic movement properties (known as process model) with a model of the observation methods (known as observation model). In this study, the Bayesian analysis was conducted on Dolly Varden Mark-recapture Data in Canadian Arctic and unbiased biological information about Dolly Varden can be summarized from mark-recapture data which can be helpful to determine if the population was sustainably harvested and build an environment friendly and sustainably fishing community.