AbstractThe ratio of the effective number of breeders (Nb) to the adult census size (Na), Nb/Na, approximates the departure from the standard capacity of a population to maintain genetic diversity in one reproductive season. This information is relevant for assessing population status, understanding evolutionary processes operating at local scales, and unraveling how life‐history traits affect these processes. However, our knowledge on Nb/Na ratios in nature is limited because estimation of both parameters is challenging. The sibship frequency (SF) method is adequate for reliable Nb estimation because it is based on sibship and parentage reconstruction from genetic marker data, thereby providing demographic inferences that can be compared with field‐based information. In addition, capture–mark–recapture (CMR) robust design methods are well suited for Na estimation in seasonal‐breeding species. We used tadpole genotypes of three pond‐breeding amphibian species (Epidalea calamita, Hyla molleri, and Pelophylax perezi, n = 73–96 single‐cohort tadpoles/species genotyped at 15–17 microsatellite loci) and candidate parental genotypes (n = 94–300 adults/species) to estimate Nb by the SF method. To assess the reliability of Nb estimates, we compared sibship and parentage inferences with field‐based information and checked for the convergence of results in replicated subsampled analyses. Finally, we used CMR data from a 6‐year monitoring program to estimate annual Na in the three species and calculate the Nb/Na ratio. Reliable ratios were obtained for E. calamita (Nb/Na = 0.18–0.28) and P. perezi (0.5), but in H. molleri, Na could not be estimated and genetic information proved insufficient for reliable Nb estimation. Integrative demographic studies taking full advantage of SF and CMR methods can provide accurate estimates of the Nb/Na ratio in seasonal‐breeding species. Importantly, the SF method provides results that can be readily evaluated for reliability. This represents a good opportunity for obtaining robust demographic inferences with wide applications for evolutionary and conservation research.