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<p>Bacterial leaf blight (BLB), caused by <i>Xanthomonas oryzae</i> pv. <i>oryzae</i>, inflicts yield losses of 10–70% in Asian rice production, necessitating sustainable alternatives to chemical control amid escalating pathogen resistance and environmental concerns. We integrated GIS-based ecological niche modelling with microbial ecology to predict the spatial distribution and habitat suitability of four bacterial families (Bacillaceae, Burkholderiaceae, Mycobacteriaceae, and Xanthomonadaceae) across Punjab Province, Pakistan, a major rice-growing region. Bacterial occurrence data (<i>n</i> = 60 sampling locations across 10 districts) derived from high-throughput 16&#xa0;S rRNA sequencing of rice rhizosphere and phyllosphere communities were coupled with 19 bioclimatic variables to develop MaxEnt species distribution models. Models demonstrated good to excellent predictive performance, Burkholderiaceae (training AUC = 0.979, test AUC = 0.967), Xanthomonadaceae (0.933, 0.801), Mycobacteriaceae (0.897, 0.625), and Bacillaceae (0.830, 0.688). Precipitation seasonality (Bio15) was the dominant predictor for Bacillaceae, Mycobacteriaceae, and Xanthomonadaceae, while annual precipitation (Bio12) governed Burkholderiaceae distribution, reflecting distinct physiological adaptations. Spatial analysis revealed pronounced niche partitioning where Bacillaceae predominated in central-southwestern Punjab (semi-arid, high precipitation seasonality); Burkholderiaceae occupied restricted northeastern zones (&gt; 1000&#xa0;mm rainfall); Mycobacteriaceae formed a continuous belt across central-eastern districts; and Xanthomonadaceae exhibited the broadest distribution in northeastern-eastern Punjab. Minimal spatial overlap among high-suitability zones indicates environmental niche differentiation with implications for region-specific biocontrol deployment. This study provides the first spatially explicit framework for targeting antagonistic bacterial communities in rice BLB management, identifying priority zones for biocontrol agent application and native microbial conservation. Integration with companion bioassay validations establishes a comprehensive foundation for precision agriculture applications in climate-resilient rice production systems.</p>

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GIS-based ecological niche modeling enables precision deployment of bacterial biocontrol agents against rice bacterial blight

  • 期刊论文

  • 发表日期：

    2025年12月19日

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  • Syed Atif Hasan Naqvi,
  • Ummad ud Din Umar,
  • Ateeq ur Rehman

摘要

Bacterial leaf blight (BLB), caused by Xanthomonas oryzae pv. oryzae, inflicts yield losses of 10–70% in Asian rice production, necessitating sustainable alternatives to chemical control amid escalating pathogen resistance and environmental concerns. We integrated GIS-based ecological niche modelling with microbial ecology to predict the spatial distribution and habitat suitability of four bacterial families (Bacillaceae, Burkholderiaceae, Mycobacteriaceae, and Xanthomonadaceae) across Punjab Province, Pakistan, a major rice-growing region. Bacterial occurrence data (n = 60 sampling locations across 10 districts) derived from high-throughput 16 S rRNA sequencing of rice rhizosphere and phyllosphere communities were coupled with 19 bioclimatic variables to develop MaxEnt species distribution models. Models demonstrated good to excellent predictive performance, Burkholderiaceae (training AUC = 0.979, test AUC = 0.967), Xanthomonadaceae (0.933, 0.801), Mycobacteriaceae (0.897, 0.625), and Bacillaceae (0.830, 0.688). Precipitation seasonality (Bio15) was the dominant predictor for Bacillaceae, Mycobacteriaceae, and Xanthomonadaceae, while annual precipitation (Bio12) governed Burkholderiaceae distribution, reflecting distinct physiological adaptations. Spatial analysis revealed pronounced niche partitioning where Bacillaceae predominated in central-southwestern Punjab (semi-arid, high precipitation seasonality); Burkholderiaceae occupied restricted northeastern zones (> 1000 mm rainfall); Mycobacteriaceae formed a continuous belt across central-eastern districts; and Xanthomonadaceae exhibited the broadest distribution in northeastern-eastern Punjab. Minimal spatial overlap among high-suitability zones indicates environmental niche differentiation with implications for region-specific biocontrol deployment. This study provides the first spatially explicit framework for targeting antagonistic bacterial communities in rice BLB management, identifying priority zones for biocontrol agent application and native microbial conservation. Integration with companion bioassay validations establishes a comprehensive foundation for precision agriculture applications in climate-resilient rice production systems.