No abstract

1. Overfishing, exacerbated by illegal, unreported, and unregulated (IUU) fishing, is a serious threat to the conservation of the Caspian sturgeon populations, exposing them to the brink of extinction. This indicates the importance of investigating the causes and eliminating the consequences of the occurrence of IUU fishing.2. This study aimed to determine the barriers to sturgeon conservation, and to evaluate the importance of variables involved in the occurrence of IUU fishing in the southern Caspian Sea using field-and questionnaire-based surveys of 520 Iranian fishers and 40 fishery experts.3. Modelling the data using the Logit regression model indicated that several social, economic, conservation, and fishery-related variables (including fisheries knowledge, fish price, fishing method, fishing time, catch/vessel ownership, conservation importance, and penalty awareness) significantly contributed to the occurrence of illegal fishing. Fishers with poorer fisheries knowledge who owned fishing vessels were more likely to be involved in IUU fishing. In addition, fishers who were less concerned about sturgeon conservation and who used non-standard fishing gear at night had a higher probability of committing IUU fishing. 4. Exploring the opinions of fishery experts through the analytical hierarchy process also showed that economic, social, fishing, and conservation criteria were respectively attributed the highest weights as the contributing criteria to the occurrence of IUU fishing. 5. Overall, close associations were observed between the range of determinants, with the probability of the occurrence of IUU fishing indicating that illegal fishing is a complex event that should be studied in different dimensions because of the involvement of a combination of drivers. The knowledge obtained here can assist the relevant agencies in preventing this widespread problem, and with the practical rebuilding and more efficient conservation planning of sturgeon stocks.

A key requirement for managing commercial fisheries is understanding the geographic footprint of the resource, the level of exploitation and the potential impacts of changing climate or habitat conditions. The development of spatially explicit predictive models of species distributions combined with predictions of changing oceanographic conditions provides the opportunity to obtain new insights of species‐habitat associations. Here, generalized linear models (GLMs) were used to model the abundance of two commercially important marine macro‐invertebrates, blacklip abalone Haliotis rubra and long‐spined sea urchin Centrostephanus rodgersii, along the coast of Victoria, Australia. We combined abundance data from fisheries independent diver surveys with environmental variables derived from bathymetric light detection and ranging (LiDAR) and oceanographic parameters derived from satellite imagery. The GLM was used to predict species responses to environmental gradients where reef complexity, sea surface temperature (SST) and depth were strongly associated with species distributions. The abundance of H. rubra declined with increasing summer SST. In comparison, the abundance of C. rodgersii increased with increasing winter SST. The GLM showed that the projected increase in ocean temperatures will likely lead to a decline in abundance across the H. rubra fishery. Conversely, a range expansion of C. rodgersii is likely due to the strengthening of the East Australian Current. For species that exhibit a high affinity to specific seascape features, this research demonstrated how recent advances in seabed mapping can allow the identification of areas with high conservation or fisheries value at a fine‐scale relevant to resource exploitation across large geographic regions.