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Integrating climate scenarios and advanced modeling to predict freshwater fish invasions: insights from Carassius species in Iran
by
Nahjafabadi, Asma Shahmoradi
, Janko, Karel
, Babookani, Mina Karimi
, Khoshnamvand, Hadi
, Abdoli, Asghar
in
631/158
/ 704/106
/ 704/158
/ 704/172
/ 704/242
/ Algorithms
/ Animals
/ Aquatic ecosystems
/ Biodiversity
/ Biological invasions
/ Carassius
/ Carassius invasions
/ Climate Change
/ Climate change scenarios
/ Climate prediction
/ Conservation of Natural Resources
/ Ecosystem
/ Ensemble machine learning
/ Environmental conditions
/ Fish
/ Fresh Water
/ Freshwater ecosystems
/ Freshwater ecosystems conservation
/ Freshwater fish
/ Geographical distribution
/ Humanities and Social Sciences
/ Hydrology
/ Inland waters
/ Introduced Species
/ Invasive fish
/ Invasive species
/ Iran
/ Machine Learning
/ Models, Theoretical
/ multidisciplinary
/ Native species
/ Nonnative species
/ Range extension
/ Science
/ Science (multidisciplinary)
/ Sea level
/ Species distribution modeling (SDM)
/ Variables
2025
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Integrating climate scenarios and advanced modeling to predict freshwater fish invasions: insights from Carassius species in Iran
by
Nahjafabadi, Asma Shahmoradi
, Janko, Karel
, Babookani, Mina Karimi
, Khoshnamvand, Hadi
, Abdoli, Asghar
in
631/158
/ 704/106
/ 704/158
/ 704/172
/ 704/242
/ Algorithms
/ Animals
/ Aquatic ecosystems
/ Biodiversity
/ Biological invasions
/ Carassius
/ Carassius invasions
/ Climate Change
/ Climate change scenarios
/ Climate prediction
/ Conservation of Natural Resources
/ Ecosystem
/ Ensemble machine learning
/ Environmental conditions
/ Fish
/ Fresh Water
/ Freshwater ecosystems
/ Freshwater ecosystems conservation
/ Freshwater fish
/ Geographical distribution
/ Humanities and Social Sciences
/ Hydrology
/ Inland waters
/ Introduced Species
/ Invasive fish
/ Invasive species
/ Iran
/ Machine Learning
/ Models, Theoretical
/ multidisciplinary
/ Native species
/ Nonnative species
/ Range extension
/ Science
/ Science (multidisciplinary)
/ Sea level
/ Species distribution modeling (SDM)
/ Variables
2025
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Integrating climate scenarios and advanced modeling to predict freshwater fish invasions: insights from Carassius species in Iran
by
Nahjafabadi, Asma Shahmoradi
, Janko, Karel
, Babookani, Mina Karimi
, Khoshnamvand, Hadi
, Abdoli, Asghar
in
631/158
/ 704/106
/ 704/158
/ 704/172
/ 704/242
/ Algorithms
/ Animals
/ Aquatic ecosystems
/ Biodiversity
/ Biological invasions
/ Carassius
/ Carassius invasions
/ Climate Change
/ Climate change scenarios
/ Climate prediction
/ Conservation of Natural Resources
/ Ecosystem
/ Ensemble machine learning
/ Environmental conditions
/ Fish
/ Fresh Water
/ Freshwater ecosystems
/ Freshwater ecosystems conservation
/ Freshwater fish
/ Geographical distribution
/ Humanities and Social Sciences
/ Hydrology
/ Inland waters
/ Introduced Species
/ Invasive fish
/ Invasive species
/ Iran
/ Machine Learning
/ Models, Theoretical
/ multidisciplinary
/ Native species
/ Nonnative species
/ Range extension
/ Science
/ Science (multidisciplinary)
/ Sea level
/ Species distribution modeling (SDM)
/ Variables
2025
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Integrating climate scenarios and advanced modeling to predict freshwater fish invasions: insights from Carassius species in Iran
Journal Article
Integrating climate scenarios and advanced modeling to predict freshwater fish invasions: insights from Carassius species in Iran
2025
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Overview
Freshwater ecosystems are increasingly imperiled by the dual pressures of biological invasions and climate change, necessitating robust predictive frameworks for effective management. This study integrates advanced ensemble machine learning (EML) within a species distribution modeling (SDM) framework to assess the current and future invasion risk of
Carassius
species (
C. auratus
,
C. gibelio
, and
C. langsdorfii
) across Iranian inland waters. A comprehensive dataset of 486 occurrence records was analyzed alongside eight rigorously selected environmental predictors encompassing climatic, topographical, hydrological, and anthropogenic variables. The BIOMOD2 R package facilitated the construction of an EML-based SDM, leveraging six algorithms weighted by AUC to maximize predictive accuracy. Model performance, evaluated via AUC and true skill statistic (TSS), demonstrated high discriminatory power. Projections under two CMIP6 climate scenarios (SSP 126 and SSP 585) reveal significant potential for range expansion and spatial redistribution of
Carassius
species, particularly under high-emission trajectories, highlighting increased invasion risks in ecologically sensitive basins. Variable importance analysis underscored the primacy of temperature, precipitation, terrain ruggedness, and human footprint in shaping invasion potential. Additionally, using kernel density estimation (KDE) analysis, the Caspian basin emerged as a critical invasion region for
Carassius
populations. These findings underscore the urgent need for targeted monitoring and management strategies and demonstrate the utility of EML-SDMs in anticipating biological invasions under global change. The integrative approach presented here provides a scalable framework for proactive biodiversity conservation and policy development in freshwater systems facing multifaceted anthropogenic threats and provides a replicable framework for forecasting biological invasions in other vulnerable freshwater systems.
Publisher
Nature Publishing Group UK,Nature Publishing Group,Nature Portfolio
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