نشریه محیط زیست طبیعی

مدل‌سازی رویشگاه بالقوه Trigonella elliptica با استفاده از متغیرهای محیطی و تکنیک‌ یادگیری ماشینی در مراتع استان یزد

نوع مقاله : مقاله پژوهشی

نویسندگان

1 گروه احیاء مناطق خشک و کوهستانی، دانشکده منابع طبیعی، دانشگاه تهران، کرج، ایران

2 اداره کل منابع طبیعی و آبخیزداری استان یزد، یزد، ایران

چکیده

رویشگاه بالقوه گیاه مرتعی شنبلیله شیرازی (Trigonella elliptica) در اراضی مرتعی استان یزد با استفاده از الگوریتم جنگل تصادفی به‌عنوان یکی از مدل‌های پیشرفته یادگیری ماشینی مدل‌سازی شد. از 11 متغیر کاربری اراضی، شاخص شوری خاک، بارندگی، حداقل و حداکثر دما، تبخیر، ارتفاع، جهت و درجة شیب، فاصله تا آبراهه و شاخص خیسی توپوگرافی و همچنین موقعیت مکانی حضور شنبلیله شیرازی استفاده شد. از مجموع 103 موقعیت مکانی ثبت‌شده به‌عنوان نقاط حضور این گیاه، به‌طور تصادفی 70 درصد برای آموزش مدل و 30 درصد برای آزمون مدل توسعه داده شده استفاده شد. به‌منظور اعتبارسنجی و آزمون مدل، از مساحت زیر منحنی مشخصه عملکرد (AUC_ROC) و جهت تعیین اهمیت متغیرهای محیطی مورد استفاده در مدل‌سازی از روش جک‌نایف (Jackknife) استفاده شد. نتایج ارزیابی مدل با استفاده از منحنی ROC (AUC>0/8)، عملکرد خیلی خوب را نشان داد. همچنین آماره‌های خطا شامل صحت، دقت مدل‌سازی، مقادیر اریبی، احتمال آشکارسازی و نرخ هشدار اشتباه به‌ترتیب 0/9، 0/79، 1، 0/93 و 0/04 را نشان دادند که بیان‌گر عملکرد خوب مدل است. نتایج تعیین اهمیت متغیرها نشان داد که به‌ترتیب عامل درجة شیب، و سپس ارتفاع و شاخص خیسی توپوگرافی نسبت به بقیة عوامل در تعیین رویشگاه بالقوه شنبلیله شیرازی اهمیت بیشتری دارند. نقشة حاصل از پیش‌بینی رویشگاه بالقوه شنبلیله شیرازی می‌تواند به‌عنوان اطلاعات دقیق به‌منظور احیاء رویشگاه‌های تخریب شده این گیاه مرتعی در استان یزد مفید واقع‌شده و مورد توجه بخش اجرایی قرار گیرد.

کلیدواژه‌ها

عنوان مقاله [English]

Spatial modeling of Trigonella elliptica potential habitat using environmental variables and machine learning technique in the Rangelands of Yazd province

نویسندگان [English]

  • Ehsan Moradi 1
  • Ali Tavili 1
  • Mohsen Asadollahi 1
  • Mohammad Reza Ahmadi Roknabadi 2

1 Department of Reclamation of Arid and Mountainous Regions, Faculty of Natural Resources, University of Tehran, Karaj, Iran

2 Bureau of Natural Resources and Watershed Management, Yazd Province, Yazd, Iran

چکیده [English]

Identifying plant species distribution and potential habitats which are under degraded in the rangelands ecosystem is an essential challenge in natural resource science. Performance these studies will support rangeland conservation, restoration, and management measures. In this study, the potential habitat of Trigonella elliptica in rangeland of Yazd province was modeled using one of the advanced machine learning models (Random Forest algorithm). We used 11 variables including land use, soil salinity index, rainfall, minimum and maximum temperature, evaporation, elevation, aspect and degree of slope, distance from river, and topographic wetness index, as well as 103 presence points of T. elliptica to improve the model. 70 % of the T. elliptica presence points were randomly selected for model training and 30% of them for model testing. In order to evaluate the model and the importance of environmental variables were used the area under the receiver operator characteristic (ROC) curve and the Jackknife methods respectively. The evaluation results of the model using the ROC curve (AUC> 0.8) showed a very good performance. Error statistics including Accuracy, Precision, Bias, Probability of Detection and False Alarm Ratio showed 0.9, 0.79, 1, 0.93 and 0.04, respectively, which demonstrate the good performance of the model to prediction. In addition, the results of determining the importance of variables showed that the slope degree and following it, elevation and topographic wetness index are more important than other variables in determining the potential habitat of T. elliptica. The map obtained from the prediction of the potential habitat of T. elliptica can be very useful as accurate information in the rangeland management in order to Reclamation the destroyed habitats of this rangeland plant in Yazd province and be highly regarded by rangeland managers.

کلیدواژه‌ها [English]

  • Spatial modeling
  • Trigonella elliptica
  • Rangelands of Yazd province
  • Random Forest
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نشریه محیط زیست طبیعی
دوره 75، شماره 2 - شماره پیاپی 2
تیر 1401
صفحه 291-306