Estimating fecundity and density dependence from mark-recapture data for making population projections

Forecasting changes in size and distributions of populations is at the forefront of ecological sciences in the 21st century. Such forecasts require robust estimators of fecundity, survival and density-dependence. While survival estimation is the main focus of mark-recapture modelling, fecundity and density dependence are rarely the subject of these models. Here, we demonstrate that these parameters can be simultaneously estimated in a Bayesian framework using only robust design mark-recapture data. Using simulated capture histories, we show that this framework (which we named CJS-pop) can estimate vital rates and their density dependence with little bias. When CJS-pop is applied to capture history data from Brown Creeper (Certhia americana), it provides estimates of fecundity that is expected from the breeding biology of this species. Finally, we illustrate that density dependence, even when estimated with uncertainty in the CJS-pop framework, regularizes population dynamics and reduces the frequent population extinctions and explosions observed under density-independent models. While CJS-pop as a whole is a useful addition to the current mark-recapture modelling toolbox, we argue that the independent components of this framework in estimating fecundity and density dependence can be integrated to other CJS frameworks, potentially creating models capable of population projections.