Climate-driven spread of giant hogweed [Heracleum mantegazzianum (Sommier & Levier) in Turkey: assessing future invasion risks under CMIP6 climate projections

气候驱动的巨型猪草[Heracleum mantegazzianum (Sommier & Levier) 在土耳其的扩散:基于 CMIP6 气候预测评估未来入侵风险

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Abstract

BACKGROUND: Biological invasions pose significant ecological and socio-economic threats globally. Heracleum mantegazzianum (giant hogweed) is an invasive plant, extensively invading Europe and North America. It exerts negative impacts on ecosystems, native vegetation, and public health in the invaded range. Although H. mantegazzianum has not been reported from Turkey yet, ecological conditions of the country similar to those prevailing in its native and invaded ranges suggest a high introduction and spread risk for Turkey. Therefore, the current study predicted the introduction and future invasion risk of H. mantegazzianum in Turkey under current and future Coupled Model Intercomparison Project Phase 6 (CMIP6) projections. METHODS: Maximum Entropy (MaxEnt) model was used to predict introduction and future invasion risk using occurrence data from native and invaded ranges and global environmental data. Only climatic data were used for modeling as future data for soil and socioeconomic attributes are currently unavailable. Multicollinearity among environmental variables was tested and 10 least correlated variables, i.e., bio1 (annual mean temperature), bio2 (mean diurnal range), bio4 (temperature seasonality), bio5 (max temperature of warmest month), bio6 (min temperature of coldest month), bio7 (temperature annual range), bio10 (mean temperature of warmest quarter), bio11 (mean temperature of coldest quarter), bio14 (precipitation of driest month), and bio15 (precipitation seasonality) were used to train and test the model. Furthermore, the model was optimized before training and testing. The model was trained and tested with 18,607 occurrence records of which 75% and 25% were split for training and testing, respectively. Future invasion risk was predicted under two CMIP6 climate change scenarios (SSP1-2.6 and SSP5-8.5). Predictive accuracy of the model was evaluated by area under the receiver operating characteristics curve (AUC), true skill statistics (TSS), sensitivity and specificity. RESULTS: MaxEnt model predicted introduction and future invasion risk of H. mantegazzianum with high accuracy (AUC = 0.97 ± 0.02; TSS = 0.94 ± 0.04, Kappa = 0.92 ± 0.03, sensitivity = 93.40 ± 2.20, and specificity = 94.80 ± 3.40). The bio14, bio6 and bio1 had the highest permutation importance indicating that temperature and precipitation changes will mediate the introduction and future invasion of H. mantegazzianum. A total 4.2% of Turkey's land area (31.2 thousand km(2)) was predicted highly suitable for the introduction of H. mantegazzianum in the Black Sea region under current climate. The CMIP6 climate projections suggest a ~ 50% decline in highly suitable habitats, and aggregation around the Black Sea coast. CONCLUSION: Climate change is expected to reduce the overall range of H. mantegazzianum in Turkey but may intensify impacts in Black Sea region due to aggregation. Proactive monitoring and management strategies targeting high invasion risk areas guided by invasion risk maps from this study are urgently needed mitigate ecological and socio-economic consequences of H. mantegazzianum in Turkey.

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