ارزیابی کارایی شاخص‌های فاصله‌ای در برآورد الگوی پراکنش مکانی در توده‌های آمیخته جنگل‌ ارسباران

نوع مقاله : مقاله پژوهشی

نویسندگان

1 گروه جنگلداری، دانشکده کشاورزی و منابع طبیعی اهر، دانشگاه تبریز

2 بخش تحقیقات جنگل‌ها و مراتع، مرکز تحقیقات و آموزش کشاورزی و منابع طبیعی آذربایجان شرقی، سازمان تحقیقات، آموزش و ترویج کشاورزی، تبریز

چکیده

نحوه پراکنش مکانی درختان یکی از مهم‌ترین ویژگی ساختاری توده جنگلی است که به‌عنوان شاخصی از مراحل توسعه، تنوع زیستی، ثبات اکولوژیکی، فرآیندهای رقابت و عملکرد کلی اکوسیستم‌های جنگلی محسوب می‌شود از این رو هرگونه تغییر در پراکنش مکانی درختان، نقش مهمی در اکوسیستم جنگل دارد. هدف پژوهش حاضر بررسی کارایی شاخص‌های فاصله تا همسایه، ابرهارت،‌ هاپکینز و جانسون-زایمر در برآورد پراکنش الگوی مکانی توده‌های طبیعی جنگلی در منطقه ارسباران بود. برای جمع‌آوری اطلاعات از عرصه، از روش فاصله‌ای نزدیکترین همسایه‌ها در 60 نقطه نمونه‌برداری استفاده شد. در هر نقطه قطر و ارتفاع درختان مرجع و سه درخت همسایه در نزدیکترین فاصله از درخت مرجع و فاصله و آزیموت بین آنها اندازه‌گیری و ثبت شد. شاخص فاصله همسایگی بین درختان نشان داد که میانگین فاصله‌های اندازه‌گیری شده 08/0 ± 2/4 متر بود و طبقه 4 تا 6 متر دارای بیشترین فراوانی در بین فواصل اندازه‌گیری شده بود. مقدار شاخص ابرهارت 08/1، شاخص ‌هاپکینز 63/0 و شاخص پراکنش جانسون-زایمر 29/1 و در نهایت الگوی پراکنش درختان، یکنواخت نشان داده شد. آزمون‌های آماری در مطالعه حاضر الگوهای پیش‌بینی شده توسط‌ این شاخص‌ها را در سطح% 95 تایید کردند. به دلیل اقدامات حفاظتی صورت گرفته در جنگل ارسباران، این منطقه می‌تواند نشان‌دهنده الگوی واقعی پراکنش گونه‌ها باشد بنابراین الگوی به‌دست آمده تا حدود زیادی قابل اطمینان خواهد بود به این ترتیب پیشنهاد می‌شود که نقشه الگوی پراکنش برای هرگونه درختی در منطقه تهیه شود، تا ضمن در اختیار قرار دادن نتایج مناسب‌تر و دقیق‌تری از ساختار توده و امکان تکمیل بانک اطلاعات اکولوژیکی منطقه، داده‌های با ارزشی در کمک به برنامه‌های مدیریتی منطقه فراهم شود.

کلیدواژه‌ها


عنوان مقاله [English]

Efficiency Evaluating of Distance Indices in Estimating Tree’s Spatial Distribution Pattern in Arasbaran Forest

نویسندگان [English]

  • Roya Abedi 1
  • Raheleh Ostad hashemi 2
1 Faculty of Agriculture and Natural Resources, University of Tabriz
2 Forest and rangelands Research Department, East Azarbaijn Agriculture and Natural Resources Research and Education Center, AREEO, Tabriz
چکیده [English]

The spatial distribution of trees is one of the most important structural features of forest stands, which considered as an indicator for sustainable development stage of stand, biodiversity, ecological stability, competition processes and the overall process of forest ecosystems. Therefore, every change in the spatial distribution of trees plays an important role in these functions. The main purpose of this study was to investigate the efficiency evaluating of the Distance to neighbor, the Eberhardt, Hopkins and Johnson-Zimmer indices in estimating the spatial distribution of natural forest stands in Arasbaran forest. The diameter and height of reference trees and three nearest neighbor, distance and the angle between the reference and neighbors trees measured in the 60 sampling points. Results showed that Distance to neighbor index indicated that the mean of measured distances between trees was 4.2 ± 0.08 meters and 4-6 meters distance had the highest frequency among the measures. The value of the Eberhardt, Hopkins and Johnson-Zimmer indices were 1.08, 0.63 and 1.29 respectively that showed uniform distribution pattern in studied stand. Statistical analysis confirmed the spatial distribution patterns predicted at 95% level by these indicators. Protective activities in the Arasbaran forest make it largely reliable to represent the actual pattern of species distribution. Therefore, it is possible to prepare a map of the distribution pattern, more appropriate and accurate results of the species stands structure and the possibility of completing the ecological database of the region and provide valuable data to assist the regional management plans.

کلیدواژه‌ها [English]

  • Arasbaran Forest
  • Distance to neighbor index
  • Eberhardt index
  • Hopkines index
  • Johnson-Zimmer index
  • Spatial distribution pattern
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