همکاری با انجمن علمی مدیریت و کنترل مناطق بیابانی ایران

نوع مقاله : مقاله پژوهشی

نویسندگان

1 دانشجوی دکتری علوم مرتع، دانشکده‌ی کشاورزی و منابع طبیعی، دانشگاه محقق اردبیلی، اردبیل، ایران

2 دانشیار دانشکده‌ی کشاورزی و منابع طبیعی، دانشگاه محقق اردبیلی،اردبیل، ایران

3 استادیار، دانشکده‌ی کشاورزی و منابع طبیعی، دانشگاه محقق اردبیلی، اردبیل، ایران

4 استادیار پژوهشی، بخش تحقیقات جنگل‌ها، مراتع و آبخیزداری، مرکز تحقیقات و آموزش کشاورزی و منابع طبیعی استان گیلان، سازمان تحقیقات، آموزش و ترویج کشاورزی (AREEO)، رشت.ایران

چکیده

این تحقیق با هدف پیش‌بینی گسترش رویشگاه گونه Festuca ovina با روش آنتروپی حداکثر و تعیین عوامل مؤثر بر انتشار آن در گرادیان ارتفاعی مراتع مغان-سبلان استان اردبیل انجام شد. 28 مکان مطالعاتی انتخاب و در هر مکان مطالعاتی 3 ترانسکت و در طول هر ترانسکت 100 متری 10 پلات یک مترمربعی با فاصله ده متر از یکدیگر برای نمونه‌برداری انتخاب شد. نمونه‌برداری خاک در هر مکان مطالعاتی، از دو عمق 15-0 و 30-15 سانتی‌متری انجام شد. خصوصیات خاک با استفاده از روش‌های آمار مکانی، خصوصیات توپوگرافی با استفاده از مدل رقومی ارتفاع، اطلاعات اقلیمی با استفاده از داده‌های هواشناسی منطقه و سنجه‌های سیمای سرزمین به کمک نقشه کاربری تهیه شد. نقشه پیش‌بینی مربوط به پراکنش گونه F.ovina با استفاده از روش مدل‌سازی آنتروپی حداکثر تهیه شد. نقش عوامل محیطی مؤثر بر پراکنش گونه با استفاده از روش جک‌نایف و منحنی‌های پاسخ بررسی گردید. متغیرهای ارتفاع، شیب، تغییرات اندازه ضریب لکه، پتاسیم عمق 30-15 و آهک عمق 15-0 بیشترین سهم را در مدل داشتند. شاخص سطح زیر منحنی (AUC) برابر 86/0 به‌دست آمد که نشان‌دهنده صحت و کارایی متوسط مدل در شناسایی مطلوب‌ترین مناطق پراکنش است. ضریب کاپای حاصل از مقایسه نقشه‌های پیش‌بینی و واقعی مقدار 72/0 به‌دست آمد که در سطح خیلی خوب است.

کلیدواژه‌ها

عنوان مقاله [English]

Modeling and determining effective factors in distribution of Festuca ovina using Maxent in rangelands of northern Ardabil province

نویسندگان [English]

  • sahar ghafari 1
  • Ardavan Ghorbani 2
  • mehdi moammeri 3
  • Raoof Mostafazadeh 3
  • Mahmoud Bidar Lord 4
  • azad Kake mami 1

1 Ph.D. Student of Rangeland Science, Faculty of Agricultural Technology and Natural Resources, University of MohagheghArdabili, Ardabil, Iran

2 Associate Professor, Faculty of agricultural technology and natural resources, University of Mohaghegh Ardabili

3 Assistant Professor, Faculty of Agricultural Technology and Natural Resources, University of MohagheghArdabili, Ardabi, Iran

4 Research Assistant Professor, Watershed Management, Forests and Rangelands Research Department, Gilan Agricultural and Natural Resources Research and Education Center, Agricultural Research, Education and Extension Organization (AREEO), Rasht, Iran

چکیده [English]

The aim of this study was to predict the habitat expansion of Festuca ovina by maximum entropy method and to determine the effective factors on its spread in the elevation gradient of Moghan-Sabalan rangelands of Ardabil province. The 28 study sites were selected and in each study site 3 transects and along each 100-meter transect 10 plots of 1 1m2 with a distance of 10 meters from each other were selected for sampling. Soil sampling in each study site was sampled from two depths of 0-15 and 15-30 cm. Soil properties using spatial statistics, topographic characteristics using digital elevation model, climatic information using meteorological data of the region, and land use measurements prepared with the help of a user map. Prediction maps related to the distribution of F.ovina were prepared using the maximum entropy modeling method. The role of environmental factors affecting the distribution of the species was investigated using the Jackknife method and response curves. Height variables, slope, patch size (coefficient of variation), potassium (15-30 cm depth), and lime (0-15cm depth) had the highest share in the model. The area under the curve index (AUC) was 0.86, which indicates the accuracy and average efficiency of the model in identifying the most desirable distribution areas. The kappa coefficient obtained from the comparison of forecast and actual maps was 0.72, which is at a very good level.

کلیدواژه‌ها [English]

  • Ecological niche modeling
  • Habitat suitability
  • Geostatistical
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