azin ahmadi

Marine ecosystems are under serious threat from climate change, which can alter species distributions, biodiversity patterns, community structure, and ecosystem functioning by affecting temperature, acidification, and current patterns. Species distribution models (SDMs) are a useful tool for ecologists to link species’ fundamental niches with environmental conditions and project potential distribution shifts under climate change scenarios. This study modeled current and future habitat suitability for the black pomfret (Parastromateus niger) using an ensemble SDM with 1,396 occurrence records and environmental data layers (depth, temperature, salinity, currents). Six algorithms (MAXENT, GAM, GLM, RF, ANN, MARS) with ensemble approach modeled species distribution under current and future semi-optimistic (RCP 4.5) and pessimistic (RCP 8.5) scenarios for both 2050s and 2100s. Models were evaluated by AUC, TSS and Cohen’s Kappa indices. According to the results, future range changes under all optimistic and pessimistic scenarios were negative. These results reveal prospective climate change impacts on the geographic range of P. niger, providing a valuable basis for science-based adaptation initiatives aimed at ensuring long-term sustainability of populations. Localized conservation and global mitigation policies are urgently needed to sustain P. nigerand reliant human communities into the future. Habitat modeling supports climate-resilient management strategies for threatened marine species

In the last few decades, the construction of fish farms on the banks of rivers has increased significantly. The purpose of this study was to investigate the quality of the inlet and outlet water of the rainbow trout farm and also to investigate the effects of the effluent on the water quality parameters of the Masouleh River located in Guilan Province. To perform this study, three stations including the control station at the entrance of the farm, the second station at the outlet of the farm effluent and the third station at a distance of less than 100 m after the outlet of the farm were sampled once every fifteen days for three months (November, December, and January 2019). The results of the study showed that the farm output water had a significant effect on water quality indices such as temperature, acidity (pH), dissolved oxygen (DO), nitrite (NO2-), nitrate (NO3-) and ammonia. The level of dissolved oxygen in the outlet water in the first two months of the sampling (5.75 ± 0.18 mg/L) had a significant decrease (P<0.05) compared to the inlet water and the acidity, nitrate, nitrite and water hardness values ​​in the outlet water (8.23 ± 0.09, 4.83 ± 0.15, 0.09 ± 0.07, 7.55 ± 0.18, respectively) showed a significant increase compared to the input water (P<0.05). Also, the comparison between the stations showed that the third station was more polluted than the other stations and the degree of water pollution decreased as the distance from the outlet increased. According to the results of this study, it can be concluded that the output of the fish farming farm has the highest level of pollution compared to other stations due to the use of low-quality commercial feed, high density, and high rearing activity in the farm and as the distance from the farm increases, the level of water pollution decreases due to the process of self-purification of the river.