جستجوی مقالات مرتبط با کلیدواژه "مدل سازی تلفیقی" در نشریات گروه "جغرافیا"

Climate change, widely acknowledged as one of the most pressing global threats in recent decades, has significantly impacted biodiversity and natural ecosystems across the planet. The use of appropriate predictive tools can greatly aid conservation managers in their efforts to protect and preserve biodiversity. In this study, we investigated the effects of climate change on the spread and distribution of Luciobarbus barbulus (Heckel, 1847), a freshwater fish species, by employing an ensemble modeling approach using the Biomod2 package. We utilized six distinct algorithms to analyze current conditions and two future scenarios for the years 2070 and 2090, specifically focusing on the Shared Socioeconomic Pathways (SSP) includes SSP1-2.6 and SSP5-8.5 scenarios. To build our predictive model, we incorporated a comprehensive dataset comprising eight variables, including climatic, topographic, and anthropogenic factors. The results indicated that the model's predictive performance was robust, with evaluation metrics—specifically the Area Under the Curve (AUC) and True Skill Statistic (TSS)—showing values ranging from very good to excellent (AUC ≥ 0.87). Our analysis revealed that the most significant factors influencing the distribution of Luciobarbus barbulus were Annual Mean Temperature (Bio 1), Annual Precipitation (Bio 12), and Mean Temperature of the Warmest Quarter (Bio 10). Alarmingly, the model forecasts a decrease in the species distribution range under both optimistic and pessimistic scenarios for the years 2070 and 2090. In conclusion, it is imperative for managers and decision-makers in the field of biodiversity conservation to recognize and address the impacts of climate change. Identifying and implementing effective measures to protect this valuable species will be essential for ensuring its survival in a rapidly changing environment.