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.

Due to the important important role that the application of mathematical programming models have in determining optimal cropping patterns, this research presents a sustainable cropping pattern that considers selected economic, environmental, and social goals together. Using a random sampling method, a sample size of 168 farmers was selected in the Sari County, Iran. Our results showed that economic, self-sufficiency, environmental, and social goals have a distinctly different impact on cropping pattern performance. Compared to the current cropping pattern, the gross margins for economic and social goals increased by nearly 11% and 2%, respectively, and the gross margins for self-sufficiency and environmental goals decreased by nearly 2% and 36%. Interestingly, it has been found that the performance of the current cropping pattern has an average positive impact of 6% if economic, self-sufficiency, environmental, and social (employment) goals are realized simultaneously.

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