Predicting the probability of avian reproductive success and its components at a nesting site

Abstract

Avian reproduction has four prime components: nesting, mating, hatching, and fledging. Predicting the probability of individual components helps in identifying the period of reproduction that would benefit from an increased conservation effort. Identification of biotic, abiotic, and sociological variables of the nesting sites is essential to calculate the component-wise success probabilities. There is no standard methodology to estimate these probability values separately. This study proposes a methodology to estimate the success probability of each component, identifies correlated environmental predictors, and provides a modelling framework to accurately predict the nesting success probabilities using Merops philippinus as a model species. Primary surveillance data and the proposed methodology indicate that the time window between the bird's nesting and mating is most vulnerable to environmental fluctuations. Both biotic and abiotic factors are crucial determinants of nesting success. Sociological factors also play a crucial role in determining the probabilities of these successes. Mating, hatching, and fledging success depend more on biotic factors than abiotic ones. Linear modelling frameworks are helpful in exploring which types of environments are better determinants of the success of a reproductive component. Artificial neural networks are useful in predicting mating, nesting, and overall reproductive success probabilities. Though the models in this study are developed using Merops philippinus data, the proposed methodology and modelling framework is also applicable for other bird species.