پهنه‌بندی حساسیت رویشگاه‌های مانگرو استان هرمزگان به مخاطرات محیطی بر اساس درصد تاج‌پوشش

نوع مقاله : علمی - پژوهشی

نویسندگان

1 استادیار، گروه علوم جنگل، دانشکده منابع طبیعی و علوم زمین، دانشگاه شهرکرد، شهرکرد، ایران

2 استادیار، مؤسسه تحقیقات جنگلها و مراتع کشور، سازمان تحقیقات، آموزش و ترویج کشاورزی، تهران، ایران.

چکیده

در پژوهش پیش­رو درجه حساسیت رویشگاه‌های مانگرو استان هرمزگان بر مبنای بررسی درصد تاج‌پوشش (به­عنوان شاخصی از مشخصه‌های ساختاری جنگل) طبقه‌بندی شد. بدین منظور با آماربرداری میدانی و ثبت قطر تاج مانگروها در قطعه­های نمونه، درصد تاج­پوشش در هر یک از قطعه­های نمونه محاسبه شد. سپس، با تجزیه و تحلیل تصاویر ماهواره‌ای و تهیه نقشه NDVI رویشگاه­های خمیر، تیاب و جاسک، بین درصد تاج­پوشش در قطعه­های نمونه و NDVI متناظر هر قطعه در سطح رویشگاه­ها رابطه رگرسیونی برقرار شد و با اجرای رابطه رگرسیونی روی نقشه NDVI هر رویشگاه، نقشه تغییرات مکانی درصد تاج­پوشش در سطح رویشگاه‌ها تهیه شد. در آخر، با استفاده از نقشه درصد تاج‌پوشش مانگروها و با استفاده از سامانه اطلاعات جغرافیایی، نقشه درجه حساسیت رویشگاه­ها در سه طبقه تاج‌پوشش کم، متوسط و زیاد تهیه شد. نتایج نشان داد که میانگین درصد تاج‌پوشش در رویشگاه‌های خمیر، تیاب و جاسک به‌ترتیب 62، 43 و 71 درصد است و بر این اساس، رویشگاه‌های جاسک و تیاب به‌ترتیب کمترین و بیشترین درجه حساسیت را نسبت­به وقوع تنش­ها و آشفتگی­های محیطی دارند. ویژگی‌های ژئومورفولوژیک محلی، مقدار رسوب­گذاری، تأسیسات و سازه‌های ساحلی، شرایط اقتصادی و اجتماعی منطقه، آلاینده­های زیست­محیطی و بالا آمدن سطح آب دریا با تأثیر بر ساختار و رویش مانگروها می­توانند از عوامل تفاوت در درجه حساسیت بین رویشگاه‌های مورد بررسی باشد. این پژوهش با تولید اطلاعات دقیق از درجه حساسیت رویشگاه‌های مانگرو هرمزگان توانسته است پیش­نیازهای اولیه برای اجرای برنامه‌های سازگاری با تغییر اقلیم و اولویت­بندی اقدامات حفاظتی و احیاء رویشگاه‌های مانگرو را فراهم کند.

کلیدواژه‌ها


عنوان مقاله [English]

Mapping the sensitivity of mangroves of the Hormozgan Province to environmental ‎hazards based on the canopy cover percentage

نویسندگان [English]

  • Davood Mafi-Gholami 1
  • Abolfazl Jaafari 2
1 Assistant Professor, Department of forest sciences, Faculty of natural resources and earth sciences, Shahrekord University, Shahrekord, Iran
2 Assistant Prof., Research Institute of Forests and Rangelands, Agricultural Research, Education and Extension Organization (AREEO), Tehran, I. R. Iran.
چکیده [English]

The present study was conducted to classify the sensitivity degree of mangrove habitats of the Hormozgan province based on canopy percentage (as an indicator of the structural characteristics of forest). For this purpose, by field survey and recording of mangrove crown diameter in the sample plots, the percentage of canopy cover in each sample plot was calculated. Then, by analyzing satellite images and mapping NDVI of habitats, a regression relation was fitted between the percentage of canopy cover in the sample plots and the corresponding NDVI values ​​at each vegetation level and by applying the regression relation on the NDVI map, canopy cover percentage spatial changes were mapped at each habitat. Finally, the map of the susceptibility of the Khamir, Tiab, and Jask habitats to three classes of low, medium and high was prepared using the mangrove canopy cover map and GIS techniques. The results showed that the average percentages of the canopy cover in the Khamir, Tiab, and Jask were 62, 43, and 71%, respectively, that indicate that Jask and Tiab have the lowest and highest sensitivity to environmental stresses and disturbances, respectively. Local geomorphologic features, sediment yield, coastal installations, economic and social conditions of the area, environmental pollutants, and sea level rise are among the influencing factors that cause differences in the degree of susceptibility between habitats. Producing accurate information on the sensitivity of mangrove habitats of Iran, this study has provided preliminary prerequisites for implementing climate change adaptation programs and prioritize conservation and restoration activities of mangroves.

کلیدواژه‌ها [English]

  • Crown
  • Geographic Information System
  • Remote sensing
  • modeling
  • NDVI‎.‎
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