Integrating climate scenarios and advanced modeling to predict freshwater fish invasions: insights from Carassius species in Iran

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F67985904%3A_____%2F25%3A00641326" target="_blank" >RIV/67985904:_____/25:00641326 - isvavai.cz</a>

Nalezeny alternativní kódy

RIV/61988987:17310/25:A2603DE1

Výsledek na webu

<a href="https://www.nature.com/articles/s41598-025-21958-8" target="_blank" >https://www.nature.com/articles/s41598-025-21958-8</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1038/s41598-025-21958-8" target="_blank" >10.1038/s41598-025-21958-8</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Integrating climate scenarios and advanced modeling to predict freshwater fish invasions: insights from Carassius species in Iran

Popis výsledku v původním jazyce

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.

Název v anglickém jazyce

Integrating climate scenarios and advanced modeling to predict freshwater fish invasions: insights from Carassius species in Iran

Popis výsledku anglicky

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.

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

—

OECD FORD obor

10602 - Biology (theoretical, mathematical, thermal, cryobiology, biological rhythm), Evolutionary biology

Projekt

—

Návaznosti

I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Rok uplatnění

2025

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název periodika

Scientific Reports

ISSN

2045-2322

e-ISSN

2045-2322

Svazek periodika

15

Číslo periodika v rámci svazku

1

Stát vydavatele periodika

GB - Spojené království Velké Británie a Severního Irska

Počet stran výsledku

13

Strana od-do

38025

Kód UT WoS článku

001606739500011

EID výsledku v databázi Scopus

2-s2.0-105020174226