مدلسازی پراکنش گونه‌ای شمشاد هیرکانی (Buxus Hyrcana Pojark) با بهره‌گیری از مدل جنگل تصادفی در جنگل‌های شمال ایران

نوع مقاله : علمی - پژوهشی

نویسندگان

1 دانشجوی دکتری علوم و مهندسی جنگل، گرایش مدیریت جنگل، دانشکده منابع طبیعی و علوم دریایی، دانشگاه تربیت مدرس، نور، مازندران، ایران.

2 دانشیار گروه علوم و مهندسی جنگل، دانشکده منابع طبیعی و علوم دریایی، دانشگاه تربیت مدرس، نور، مازندران، ایران

3 دانشیار گروه علوم و مهندسی جنگل، دانشکده منابع طبیعی و علوم دریایی، دانشگاه تربیت مدرس، نور، مازندران، ایران.

چکیده

مقدمه و هدف: ثبات و پایداری بوم­سازگان­ها نیازمند شناخت روابط بین پراکنش گونه­های گیاهی و عوامل محیطی است. تکنیک‌های مدلسازی پراکنش گونه‌ها به­عنوان ابزار قدرتمندی برای حمایت از استراتژی­های مدیریت جنگل در زمینه تغییرات اقلیمی شناخته می­شوند. شمشاد گونه­ای بردبار به سایه بوده و در زیر آشکوب جنگل­های جلگه‌ای و میان‌بند شمال ایران پراکنش دارد که با ایجاد تاج‌پوشش انبوه و فشرده، محیطی تاریک در جنگل ایجاد می­کند. به دلیل تخریب گسترده رویشگاه­های شمشاد در دهه­های اخیر، این گونه جزء جوامع ذخیره­گاهی درنظر گرفته شده است تا از انقراض آن جلوگیری شود. هدف اصلی این پژوهش مدلسازی پراکنش این گونه در جنگل­های هیرکانی است.
مواد و روش‌ها: در این بررسی، با استفاده از 570 نقطه حضور واقعی شمشاد در جنگل‌های هیرکانی، پراکنش این گونه مدلسازی شد. متغیرهای زیست‌اقلیمی از پایگاه WorldClim و متغیرهای توپوگرافی از مدل رقومی ارتفاع استخراج شدند. برای کاهش هم‌خطی، از آزمون VIF استفاده شد. 70 درصد نمونه­ها به­عنوان داده­های آموزشی برای توسعه مدل و30 درصد باقی­مانده به­عنوان داده­های آزمون برای اعتبارسنجی مدل اختصاص داده شدند. مدلسازی با الگوریتم جنگل تصادفی در محیط R و با بهره‌گیری از داده‌های حضور و شبه غیاب، تنظیم شاخص­های مدل (500 درخت، 2=mtry، 5=min_n) و اعتبارسنجی متقابل آن با روش (10 fold Cross-Validation) انجام شد. عملکرد مدل با شاخص‌های AUC، TSS، دقت کلی و ضریب کاپا ارزیابی شد.
یافته‌ها: نتایج حاصل از مدل جنگل تصادفی نشان داد که مدل از دقت بالایی در پیش‌بینی پراکنش شمشاد برخوردار است (98/0=AUC، 95/0= Accuracy ، 72/0= Kappa ، 63/0=TSS). مدل جنگل تصادفی با استفاده از متغیرهای زیست‌اقلیمی و توپوگرافی، عملکرد بسیار مطلوبی در پیش‌بینی پراکنش شمشاد هیرکانی داشت. ارزیابی اهمیت متغیرها نشان داد که متغیرهای زیست‌اقلیمی bio3 (هم­دمایی)، bio12 (بارندگی سالانه)، bio8 (میانگین دما در فصل مرطوب) و bio1 (میانگین دمای سالانه)  بیشترین تأثیر را در پراکنش گونه شمشاد داشتند. منحنی پاسخ گونه شمشاد نسبت به چهار متغیر مهم نیز رسم شد. نقشه مطلوبیت زیستگاه شمشاد، مناطق با شرایط بوم­شناختی مناسب را مشخص کرد که بخش‌های گسترده‌ای از استان مازندران و نواحی مرزی جنگل‌های هیرکانی را شامل می‌شود.
نتیجه‌گیری: تحلیل اهمیت متغیرها نشان داد که هم‌دمایی (Bio3) به‌عنوان مؤثرترین متغیر، نشان‌دهنده نقش ثبات دمایی در زیست‌پذیری شمشاد است؛ گونه‌ای همیشه‌سبز و سایه‌پسند که در برابر نوسانات دمایی حساس است و در مناطق با دامنه دمایی متعادل (۱۵–۲۰ درجه) حضور بیشتری دارد. بارندگی سالانه (Bio12) نیز اهمیت بالایی داشت و منحنی پاسخ نشان داد احتمال حضور شمشاد در نواحی با بارندگی بیش از 300 میلی‌متر به‌مراتب بیشتر است؛ زیرا رطوبت کافی برای رشد، فتوسنتز و کاهش تنش آبی فراهم می‌سازد. متغیر Bio8 (میانگین دما در فصل مرطوب) با تأثیرگذاری بر رشد رویشی و مقاومت به بیماری‌های قارچی، در بازه دمایی حدود پنج تا ۱۰ درجه شرایط بهینه برای این گونه فراهم می‌کند. همچنین Bio1 (میانگین دمای سالانه) نشان داد که شمشاد بیشتر در مناطقی با اقلیم معتدل و دمای متوسط سالانه بین هشت تا ۱۳ درجه پراکنش دارد. در مقابل، متغیرهای توپوگرافی مثل طول شیب و تابش خورشیدی نقش مکمل داشته و در سطوح محلی شرایط میکروکلیمایی را تعدیل می‌کنند. نقشه مطلوبیت رویشگاه نیز نشان داد که مناطق میانی و غربی جنگل‌های هیرکانی، به‌ویژه در استان‌های مازندران و گیلان، دارای بالاترین احتمال حضور گونه هستند. همچنین در برخی نواحی استان گلستان نیز مطلوبیت متوسط تا بالایی پیش‌بینی شد که قابلیت بالقوه برای احیای شمشاد در این مناطق را نشان می‌دهد. این نتایج نقش کلیدی اقلیم، به‌ویژه ترکیب دما و رطوبت، را در تبیین پراکنش شمشاد تأیید کرده و بر لزوم حفاظت از زیستگاه‌های با شرایط اقلیمی پایدار تأکید می­کند.

کلیدواژه‌ها

موضوعات

عنوان مقاله [English]

Species distribution modeling of Hyrcanian boxwood (Buxus Hyrcana Pojark) using the random forest model in the forests of northern Iran

نویسندگان [English]

  • Aref Hesabi 1
  • Seyed Jalil Alavi 2
  • Omid Esmailzadeh 3
1 PhD Student of Forest Management, Department of Forest Science, Faculty of Natural Resources and marine science, Tarbiat Modares University, Nur, Mazandaran, I. R. Iran
2 Associate Professor, Department of Forest Science, Faculty of Natural Resources and marine science, Tarbiat Modares University, Nur, Mazandaran, I. R. Iran
3 Associate Professor, Department of Forest Sciences and Engineering, Faculty of Natural Resources and Marine Sciences, Tarbiat Modares University, Nur, Mazandaran, I. R. Iran
چکیده [English]

Background and Objective: The stability and sustainability of ecosystems require understanding the relationships between the distribution of plant species and environmental factors. Species distribution modeling techniques are recognized as powerful tools to support forest management strategies in the context of climate change. Boxwood is a shade-tolerant species that is distributed in the understory of lowland and middle-altitude forests of northern Iran, where it creates a dark environment in the forest by forming a dense canopy. Due to the widespread destruction of boxwood habitats in recent decades, this species has been considered part of conservation communities to prevent its extinction. The main objective of this research is to model the distribution of this species in the Hyrcanian forests.
Material and Methods: In this study, the distribution of boxwood was modeled using 570 actual occurrence points in Hyrcanian forests. Bioclimatic variables were extracted from the WorldClim database and topographic variables from the digital elevation model. VIF test was used to reduce collinearity. 70% of the samples were assigned as training data for model development and the remaining 30% as test data for model validation. Modeling was performed using the random forest algorithm in R environment and using presence and pseudo-absence data, adjusting the model parameters (500 trees, mtry=2, min_n=5) and validating it by using the 10-fold Cross-Validation method. Model performance was evaluated with AUC, TSS, overall accuracy, and kappa coefficient.
Results: The results of the Random Forest model showed that the model has high accuracy in predicting the distribution of boxwood (AUC=0.98, Accuracy=0.95, Kappa=0.72, TSS=0.63). The random forest model, using bioclimatic and topographic variables, showed very favorable performance in predicting the distribution of Hyrcanian boxwood. Evaluation of variable importance indicated that the bioclimatic variables bio3 (isothermality), bio12 (annual precipitation), bio8 (mean temperature of the wettest quarter) and bio1 (annual mean temperature) had the greatest impact on the distribution of the boxwood species. The response curve of boxwood to the four important variables was also plotted. The boxwood habitat suitability map identified areas with suitable ecological conditions, including large parts of Mazandaran province and the border areas of the Hyrcanian forests.
Conclusion: Analysis of variable importance showed that isothermality (Bio3) was the most effective variable, indicating the role of thermal stability in the viability of boxwood; an evergreen and shade-loving species that is sensitive to temperature fluctuations and is more present in areas with a balanced temperature range (15–20 degrees). Annual precipitation (Bio12) was also of high importance, and the response curve showed that the probability of boxwood presence is much higher in areas with precipitation above 300 mm; because it provides sufficient moisture for growth, photosynthesis, and reduction of water stress. Variable Bio8 (mean temperature of the wettest quarter) by affecting vegetative growth and resistance to fungal diseases, provides optimal conditions for this species in the temperature range of about 5 to 10 degrees. Also, Bio1 (annual mean temperature) showed that boxwood is more distributed in areas with temperate climates and an average annual temperature between 8 and 13 degrees. In contrast, topographic variables such as slope length and solar radiation played a complementary role and moderated microclimatic conditions at the local level. The habitat suitability map also showed that the central and western regions of the Hyrcanian forests, especially in the provinces of Mazandaran and Gilan, have the highest probability of species presence. Also, in some areas of Golestan province, medium to high suitability was predicted, which shows the potential for boxwood restoration in these areas. These results confirm the key role of climate, especially the combination of temperature and humidity, in explaining the distribution of boxwood and emphasize the need to protect habitats with stable climatic conditions.

کلیدواژه‌ها [English]

  • Bioclimatic variable
  • Habitat suitability
  • Machine learning
  • Worldclim database

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پژوهش و توسعه جنگل
دوره 11، شماره 3
آذر 1404
صفحه 353-375

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