مدل سازی توزیع پتانسیل گونه Juniperus excelsa با استفاده از عامل های محیطی در کوهستان البرز

نوع مقاله : مقاله پژوهشی

نویسندگان

1 گروه بیابان زدایی، دانشکده کویرشناسی، دانشگاه سمنان، سمنان، ایران

2 گروه مرتع و آبخیزداری، دانشکده منابع طبیعی، دانشگاه صنعتی اصفهان، اصفهان، ایران

3 بخش تحقیقات جنگل، موسسه تحقیقات جنگل‌ها و مراتع کشور، سازمان تحقیقات، آموزش و ترویج کشاورزی، تهران، ایران

چکیده

سابقه و هدف:
مدل ­سازی توزیع گونه‌ای، روشی رایج برای درک روابط میان یک گونه و محیط اطرافش است و برای پیش‌بینی تغییرات در توزیع همگام با تغییرات محیطی مورد استفاده قرار می‌گیرد. تحقیق­ های گسترده‌ای در منطقه ­های مختلف دنیا براساس این مدل‌ها انجام گرفته است. در این مطالعه، توزیع پتانسیل گونه ارس1، گونه سنجه و یکی از مهم ترین گونه‌های درختی جنگل‌های ایران و تورانی، در کوهستان البرز با استفاده از 38 پارامتر محیطی با استفاده از مدل‌های توزیع گونه‌ای  Domain و رگرسیون لجستیک2 مورد بررسی قرار گرفته است.
 مواد و روش‌ها:
منطقه مورد مطالعه، شامل بخش‌هایی از کوهستان البرز است که در شمال ایران واقع شده و دارای مساحتی برابر با 14656 کیلومترمربع می‌باشد. در تحقیق حاضر، برای تعیین سایت‌های نمونه‌برداری، از روش تصادفی طبقه‌بندی شده استفاده گردید و در نهایت تعداد 390 سایت رخداد (240 سایت حضور و 150 سایت عدم حضور) گونه Juniperus excelsa در مقیاس 30 ثانیه (کمابیش معادل 1کیلومتر* 1 کیلومتر) به‌عنوان ورودی مدل مورد مطالعه قرار گرفت. همچنین، تعداد 38 پارامتر محیطی به ­عنوان متغیر پیش‌بینی‌کننده برای اجرای دو مدل Domain و Logistic Regression مد نظر قرار گرفت.
نتایج و بحث:
نتایج نشان داد که مدل Domain کارایی بالایی برای پیش‌بینی رویشگاه Juniperus excelsa با 0.97 AUC=، Kappa=0.730 و TSS=0.91 داراست. براساس نتایج به ­دست آمده، منطقه ­های با کمترین پتانسیل حضور Juniperus excelsa 5665.95 کیلومتر مربع، پتانسیل متوسط 2033.1 کیلومتر مربع، پتانسیل خوب، 38/3076 کیلومترمربع، پتانسیل بسیار خوب 42/3063 کیلومترمربع و پتانسیل عالی 817.29 از سطح منطقه را به خود اختصاص داده‌اند. نتایج به‌دست آمده از اجرای مدل رگرسیون لجستیک گویای آن است که 5084.37 کیلومتر مربع از منطقه مورد مطالعه در طبقه پتانسیل ضعیف، 2539.35 کیلومتر مربع پتانسیل متوسط، 1410.21 پتانسیل خوب و 1104.84 کیلومترمربع پتانسیل بسیار خوب و 37/4517 کیلومترمربع پتانسیل عالی قرار گرفته است. همچنین نتایج نشان داد که شرایط مطلوب رویشگاهی گونه Juniperus excelsa در منطقه­ هایی است که اختلاف حداکثر و حداقل درجه حرارت سالانه بین 15.5 تا 13 درجه سانتی‌گراد، بارش فصلی 90 - 64 میلی‌متر، بارش سردترین فصل سال 60 - 35 میلی‌متر، ارتفاع از سطح دریا، 3100 - 1800 متر، در جهات جغرافیایی جنوب، جنوب شرق و شرق، شیب 30 - 10 درصد است، همچنین احتمال حضور گونه در منطقه­ هایی که کمترین فاصله را با خط برف و آبراهه دارند و روی صخره‌هایی از جنس آهک شیلی و آهک دولومیتی افزایش می‌یابد. همچنین، در بخش‌هایی از منطقه که گونه Juniperus excelsa مشاهده می‌شود، سنجه NDVI بین 0.38 تا 0.2 تغییر می‌نماید. نتایج ارزیابی عملکرد مدل‌ها، نشان داد که مدل Domain دارای کارایی بالاتری در پیش‌بینی رویشگاه مطلوب گونه Juniperus excelsa نسبت به مدل رگرسیون لجستیک در منطقه مورد مطالعه می‌باشد که با نتایج Hernandez et al. (2006) و Tsoar et al. (2007) که عملکرد بالای این مدل را نشان دادند، تطابق دارد.
نتیجه‌گیری:
با بکارگیری مدل توزیع گونه‌ای می‌توان برنامه مدیریتی مناسب برای بخش‌های مختلف رویشگاه را بیان نمود. منطقه ­های با پتانسیل ضعیف، به ­طور معمول رویشگاه حدی گونه هستند و جمعیت‌ها در این منطقه ­ها آسیب­پذیرتر از دیگر منطقه ­ها هستند؛ منطقه­ های با پتانسیل بسیار خوب و عالی مناسب مدیریت به ­صورت ذخیره‌گاه جنگلی یا منطقه حفاظت شده هستند. برای جنگل کاری و توسعه و احیای اکوتیپ بومی، عرصه‌هایی در مناطق با پتانسیل خوب تا عالی که بدون پوشش درختی قابل توجه هستند، مناسب می­ باشند. تحقیق حاضر نشان داد که مدل Domian با وجود آنکه تنها از داده‌های حضور استفاده می‌کند، می‌تواند روش مفیدی جهت پیش‌بینی رویشگاه‌های مطلوب گونه Juniperus excelsa در کوهستان البرز باشد. بنابراین می‌توان اظهار نمود که مدل‌های توزیع گونه‌‌ای، با دقت قبل قبولی کارایی لازم را در برآورد پراکنش گونه داشته و می‌توانند جهت بیان راهکارهای حفاظتی توسط متخصصان مورد استفاده قرار گیرند.

کلیدواژه‌ها

عنوان مقاله [English]

Modeling the potential distribution of Juniperus excelsa using environmental factors in Alborz Mountains

نویسندگان [English]

  • Samira Sadat Fatemi Azarkhavarani 1
  • Mohammad Rahimi 1
  • Mostafa Tarkesh 2
  • Hooman Ravanbakhsh 3
1 Department of Combat Desertification, Faculty of desert studies, Semnan University, Semnan, Iran
2 Department of Range & Watershead Management, Faculty of Natural Resources, Isfahan University of Technology, Isfahan, Iran
3 Department of Forest Researches, Research Institute of Forests and Rangelands, Agricultural Research, Education and Extension Organization (AREEO), Tehran, Iran
چکیده [English]

Introduction:
Species distribution modeling is a common method for understanding the relationships between a species and its environment and is used to predict the changes in distribution due to environmental changes. A lot of research has been done around the world based on these models. In this study, the optimal habitat of Juniperus excelsa, an indicator species, and the most important tree species in Irano-Turanian forests in the Alborz Mountains have been investigated using 38 environmental parameters and domain and logistic regression models.
Material and methods:
The study area consists of parts of the Alborz Mountains located in the north of Iran with an area of 14656 km2. In the present study, a stratified random sampling method was used to determine the sampling sites. Finally, 390 occurrence sites (240 presence sites and 150 absentee sites) of J. excelsa at a 30-second scale (approximately 1 km×1 km) as the input model was studied. Also, 38 environmental parameters were considered as predictive variables for implementing two models of the domain and logistic regression.
Results and discussion:
The results showed that the domain model had a high performance for predicting the habitat of J. excelsa with AUC =0.97, Kappa =0.730, and TSS = 0.91. Based on the results, the areas with the lowest potential for the presence of J. excelsa were 5665.95 km2, the moderate potential was 2033.1 km2, the good potential was 3076.38 km2, the very good potential was 3063.42 km2, and the high potential was 817.29 km2. The results obtained from the implementation of the logistic regression model indicated that 5084.37 km2 of the studied area was in the class of least potential, 2539.35 km2 had moderate potential, 1410.21 km2 had good potential, 1104. 84 km2 had very good potential, and 4517.37 km2 had high potential. Also, the results showed that the suitable habitats for J. excelsa were regions with a mean diurnal range of 13 °C and 15.5 °C, annual precipitation of 120-220 mm, precipitation of 64-90 mm, precipitation of coldest quarter of 35-60 mm, the altitude from the sea level of 3100-1800 m, and a slope of 30-10% in the southern, southeast, and east directions. Also, the probability of species occurrence was more in areas near the snow and water line as well as on calcic rocks. Also, in the habitat of J. excelsa the NDVI index varied between 0.38 and 0.20. The results of the performance evaluation of the models showed that the domain model had higher performance in predicting the suitable habitat of J. excelsa than the logistic regression model in the study area.
Conclusion:
Species distribution models can provide a suitable management plan for different parts of the habitat. Areas with low potential of suitable habitat are usually partial habitats and populations in these areas are more vulnerable than the others, whereas areas with very good potential are excellent for a protected area. Areas with good to the excellent potential that do not have significant tree cover are suitable for forestry and native ecosystem restoration. The present study showed that the domain model, despite using only presence data, can be a useful method for predicting the suitable habitat of J. excelsa in the Alborz Mountains. Therefore, it can be stated that species distribution models, with acceptable accuracy, have enough performance in the evaluation of species distribution and can be used to execute conservation strategies.

کلیدواژه‌ها [English]

  • Domain model
  • Environmental data
  • Irano-Turanian forests
  • Logistic regression

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فصلنامه علوم محیطی
دوره 18، شماره 2
تیر 1399
صفحه 237-254

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