Importance of vegetation index in codling moth Cydia pomonella distribution modeling

نوع مقاله : مقاله پژوهشی


1 Department of Plant Protection, Faculty of Agriculture, University of Tabriz, Tabriz, Iran

2 Department of Remote Sensing & GIS, Faculty of Planning and Environmental Sciences, University of Tabriz, Tabriz, Iran


Codling moth, Cydia pomonella L. (Lepidoptera: Tortricidae) is the key insect pest of apple orchards in Iran. This study was conducted in the main apple-growing regions of East Azarbaijan Province to generate potential habitat suitability maps of C. pomonella using MaxEnt modeling and to determine the importance of vegetation index in improving the accuracy of these models. Field surveys for collecting the occurrence data of codling moth were conducted during three growing seasons, 2017 - 2019. The activity of codling moth adult males was monitored using delta-shaped traps baited with female sex pheromone. Fifteen environmental variables were considered as potential predictors for estimating codling moth distribution. These variables were categorized into topographic, climatic, and remote sensing variables. A MaxEnt modeling algorithm was used to predict the distribution of codling moth. Model performance was evaluated using the area under the receiver operating characteristic curve (AUC). By using the topographic, climatic, and topographic+climatic variables, the AUC values were 0.840, 0.951, and 0.938, respectively. The model including normalized difference vegetation index (NDVI) had the highest AUC value (0.99), which strongly supports model predictive power and indicates the importance of vegetation index in codling moth distribution modeling. NDVI was the most contributed variable in the model followed by precipitation of September, slope, minimum temperature of May, and mean temperature of April. The distribution map obtained in MaxEnt provides an important tool for identifying potential risk zones of codling moth. This map can assist managers in forecasting and planning control measures and therefore, effective management of current infestations of codling moth.


عنوان مقاله [English]

اهمیت شاخص پوشش گیاهی در مدل‌سازی پراکنش کرم سیب Cydia pomonella

نویسندگان [English]

  • Hakimeh Shayestehmehr 1
  • Roghaiyeh Karimzadeh 1
  • Bakhtiar Feizizadeh 2
  • Shahzad Iranipour 1
1 Department of Plant Protection, Faculty of Agriculture, University of Tabriz, Tabriz, Iran
2 Department of Remote Sensing & GIS, Faculty of Planning and Environmental Sciences, University of Tabriz, Tabriz, Iran
چکیده [English]

کرم سیب آفت کلیدی باغ‌های سیب در ایران می‌باشد. این مطالعه در مناطق اصلی سیب‌کاری استان آذربایجان شرقی، با هدف تهیه نقشه زیستگاه‌های بالقوه این آفت با استفاده از مدل‌سازی مکس‌انت و تعیین نقش شاخص پوشش گیاهی در بهبود دقت این مدل‌ها انجام شد. داده‌های حضور آفت طی سه فصل رشدی، 98-96 از مناطق مورد مطالعه جمع‌آوری شدند. از تله های فرمونی برای پایش فعالیت حشرات کامل نر کرم سیب استفاده  شد. اثر 15 متغیر محیطی شامل متغیرهای اقلیمی، توپوگرافیک و سنجش از دور با استفاده از الگوریتم مکس‌انت روی پراکنش کرم سیب بررسی شد. عملکرد مدل‌ها و بررسی صحت و دقت آنها با استفاده از شاخص سطح زیر منحنی مشخصه عملکرد گیرنده (ROC) ارزیابی شد. در مدل‌های اجرا شده با استفاده از متغیرهای اقلیمی و توپوگرافیک مقدار AUC به ترتیب 840/0 و 951/0 بود، با تلفیق این دو گروه متغیر مقدار AUC مدل به 938/0 رسید. مدلی که دربرگیرنده هر سه گروه متغیرهای اقلیمی، توپوگرافیک و شاخص پوشش گیاهی تفاضلی نرمال شده (NDVI) بود بیشترین مقدار AUC را داشت ( که نشان دهنده نقش مهم این شاخص در پیش‌بینی پراکنش بالقوه کرم سیب است. NDVI، بارندگی ماه سپتامبر، شیب، حداقل دمای می و میانگین دمای آوریل به ترتیب بیشترین سهم را در مدل نهایی و بیشترین ارتباط را با پراکنش کرم سیب داشتند. نقشه پراکنش به دست آمده در این مطالعه ابزار مفیدی برای تشخیص مناطق خطر بالقوه کرم سیب می‌باشد که می‌تواند در پیش‌آگاهی و برنامه‌های مدیریت این آفت مهم مورد استفاده قرار گیرد.

کلیدواژه‌ها [English]

  • پراکنش گونه
  • مدل‌سازی نیچ
  • نقشه خطر
  • مدیریت آفت
  • پیش آگاهی
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