The estimation of reliable indices of abundance for sedentary stocks requires the incorporation of the underlying spatial population structure, including issues arising from the sampling design and zero inflation. We applied seven spatial interpolation techniques [ordinary kriging (OK), kriging with external drift (KED), a negative binomial generalized additive model (NBGAM), NBGAM plus OK (NBGAM+OK), a general additive mixed model (GAMM), GAMM plus OK (GAMM+OK) and a zero-inflated negative binomial model (ZINB) ] to three survey datasets to estimate biomass for the gastropod Aliger gigas on the Pedro Bank Jamaica. The models were evaluated using 10-fold cross-validation diagnostics criteria for choosing the best model. We also compared the best model estimations against two common design methods to assess the consequences of ignoring the spatial structure of the species distribution. GAMM and ZINB were overall the best models but were strongly affected by the sampling design, sample size, the coefficient of variation of the sample and the quality of the available covariates used to model the distribution (geographic location, depth and habitat). More reliable abundance indices can help to improve stock assessments and the development of spatial management using an ecosystem approach.

Context Density-dependent marine sedentary species exhibit heterogeneous distribution in response to biological needs and exploitation. Sustainable management requires consideration of factors influencing this distribution, including Allee effects and source–sink dynamics. Aim This study investigates the implications of the Allee effect and source–sink dynamics in the management of a sedentary species, queen conch (Aliger gigas) on the Pedro Bank Jamaica. Method We used spatial analysis of spatio-temporal survey data obtained over an 11-year period to determine spatial distribution and preferences. A depensation model along with knowledge of the connectivity of the population was used to model the Allee effect and define source and sink areas. Key results We found that mate-finding Allee effects and exploitation are major drivers of source–sink dynamics in this population. Sources (the effective spawning stock) consisted of less than 30% of total adult population and were being driven to a low-density stable state because of intensification of the Allee effect from high exploitation. Conclusions Management must explicitly consider Allee effects and source–sink dynamics to avoid overestimations of stock productivity and spatial mismatches of biological and management units. Stocks should be managed well above determined critical-density thresholds because stocks are unlikely to recover once they fall below them.