ensemble modeling

Evidence for the negative impacts of climate change on biodiversity is mounting, showing that climate change is one of the greatest threats to global biodiversity (Chen et al., 2011; Dubey and Shine,2011; Hannah, 2015; Terribile et al., 2018; Archis et al., 2018). Climatechange can affect the diversity and composition of species within bothterrestrial and aquatic ecosystems (Diaz et al., 2003; Dijkstra et al., 2011; Ruiz-Labourdette et al., 2013;Hannah, 2015; Liu et al., 2018). It is predicted that some species will become more dominant while others will decline or disappear (Hannah, 2015). While the negative impact of climate change is well documented on some taxonomic groups like vertebrates and plants species (Hannah, 2015) little is known about the negative impacts of climate change on fungi and macro fungi(Shrestha et al., 2014; Burgess et al., 2017; Gao et al., 2019; Hao et al.,2020).Macro fungi are important components of ecosystems and play important roles in nutrient cycling, decomposition, symbiosis, and food sources for many animals and humans. However, climate change can have negative impacts on macro fungi, such as altering their distribution and diversity thus, it is necessary to investigate potential impacts of climate change on them (Cao et al., 2021). Recent studies have shown that climate change will have negative impacts on Iran’s biodiversity (Yousefi et al., 2019).  However, little is known about the potential impacts of climate change on the diverse taxonomic groups in the country particularly macro fungi (Yousefi et al., 2019). Thus, the aim of this study is to predict the impact of climate change on distribution of the genus Trametes in north of Iran. 

Distribution records of the genus Trametes were collected during our fieldwork from 2000 to 2022 in Iran. Current and future climate data (Annual Mean Temperature (Bio1), Mean Diurnal Range (Mean of monthly (max temp - min temp)) (Bio2), Isothermality (Bio3), Temperature Seasonality (Standard Deviation) (Bio4), Annual Precipitation (Bio12), Precipitation of Driest Month (Bio14), Precipitation Seasonality (Coefficient of Variation) (Bio15)) were obtained from CHELSA high resolution climatologies version 2.1 (Kargeret al., 2017). For future climate we considered following five CMIP6 (the Coupled Model Intercomparison Project Phase 6) Global Circulation Models (GCMs): GFDL-ESM4, IPSL-CM6A-LR, MPI-ESM1-2-HR, MR-ESM2-0, UKESM1-0-LL. We applied an ensemble approach, using four distribution modeling methods (Generalized Linear Models (McCullagh & Nelder 1989), Generalized Additive Models (Hastie & Tibshirani 1990), Maximum Entropy Modelling (Phillips et al. 2006) and Random Forest (Breiman 2001)) to predict the impacts of climate change on distribution pattern of the genus. We also identified the most important climatic predictor of the genus distribution (Phillips et al. 2006). In this study AUC and TSS were used to assess the performance of the model.

According to the AUC and TSS the model performed well (AUC=0.942 and TSS=0.811). The model showed that under current climate the genus has 36,456km2 suitable habitats but the genus suitable habitats will decrease to 14,749 km2. We found that the genus will lose 60% of its suitable habitat under the climate change (2070 SSP585). Our results are in line with previous studies that have shown that fungi species will lose their suitable habitats under future climate change. For instance, Gua et al. (2017) have shown that Tricholoma matsutake will lose considerable proportions of its suitable habitat due to climate change. However, it is predicted that some species like Ophiocordyceps sinensis will expand their range under the changing climate (Shrestha and Bawa, 2014). Results also showed that precipitation of driest month and precipitation seasonality are the most important predictors of the genus distribution. These findings are also in line with previous studies that have identified temperature and precipitation of driest and warmest months as the most important determinants of fungi species distribution (Yuan et al.,2015; Yuan et al., 2019).

Iran is a biodiversity rich country in Asia hosting high diversity of macro fungi (Ghobad-Nejhad et al., 2020). In this study for the first time, we predicted the negative impacts of climate change on macro fungi in Iran. We believe that the stable suitable habitats identified in this study for the genus Trametes have high priority for conservation of the genus in Iran under the changing climate.

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.