جستجوی مقالات مرتبط با کلیدواژه "مکسنت" در نشریات گروه "شیلات"

Natural habitats around the world have suffered a lot of pressure due to the increase in human industrial activities in order to achieve economic-welfare goals, by changing in the climate system, and the consequences of this event include the extinction of species and the reduction of biodiversity on a global scale. In this regard, the evaluation of the threats resulting from the changes created in the ecosystems will be pivotal to their management and conservation. In this study, the distribution of Rutilus kutum was predicted under two optimistic and pessimistic scenarios of 2050 and 2080 by Maxent model. In this study, the set of data collected by the authors and various available scientific sources from a period of 50 years (1970 to 2020 AD) was used. Also, the environmental and climate variables used in the modeling were extracted and prepared from www.worldclim.org.The results showed that the performance of the model in predicting species distribution was excellent (0.946) based on the AUC (Area Under the Curve) criterion. In addition, it is predicted that the distribution of the species is likely to decrease significantly in all years and optimistic and pessimistic scenarios. Therefore, considering the importance of the sim species in the food basket and its positive effect on the livelihoods of local communities, reducing its distribution in the future could be considered a threat to food security. In conclusion, the protection of this species requires urgent planning, actionable decisions and effective measures regarding the preservation and restoration of rivers, controlling the negative effects of climate change and efforts to reduce the accelerating factors of this critical phenomenon.

In this study, environmental and climatic variables were used as independent variables to determine the habitat suitability of Cyprinion tenuiradius in Fars Province and to investigate the impact of climate change on its distribution. Modelling was conducted in an R software environment using the MaxEnt algorithm. Based on the results, the performance and accuracy of modelling were good (AUC = 0. 790). Also, the mean annual temperature and annual precipitation were the most important variables in determining the habitat suitability and distribution of this species, respectively. According to the species prediction under optimistic and pessimistic scenarios of climate change in 2050 and 2080, it is expected that the distribution range of this species will decrease slightly under the optimistic scenario of 2050 and 2080. However, the distribution range under the pessimistic scenario of 2050 will be increased slightly while in the pessimistic scenario of 2080, its suitable habitats will be significantly increased. It is recommended to use the obtained results for management and conservation purposes.