تحلیل میزان اثرگذاری عوامل زیست محیطی بر رویش قطری راش (Fagus orientalis lipsky) با استفاده از شبکه‌های عصبی مصنوعی در جنگل‌های استان مازندران

نوع مقاله : مقاله پژوهشی

نویسندگان

1 استادیار پژوهشی، مؤسسة تحقیقات جنگل‏ها و مراتع کشور، سازمان تحقیقات، آموزش و ترویج کشاورزی، تهران، ایران

2 دانش آموختة کارشناسی ارشد، گروه جنگلداری، دانشکدة منابع طبیعی، دانشگاه تهران، کرج، ایران

3 کارشناس ارشد، مؤسسة تحقیقات جنگل‏ها و مراتع کشور، سازمان تحقیقات، آموزش و ترویج کشاورزی، تهران، ایران

چکیده

 رویش قطری و حجمی توده­های جنگلی اساس تعیین میزان برش سالانه در برنامه­ریزی و مدیریت بهره­برداری چوب از جنگل بوده و تعیین آن و عوامل مؤثر بر روی آن یکی از مهم­ترین چالش­ها در جنگل است. در این پژوهش با استفاده از تکنیک شبکۀ عصبی مصنوعی، تأثیر متغیرهای محیط­زیستی بر رویش قطری راش در قطعات نمونۀ ثابت در جنگل­های شمال ایران، برای یک دورۀ نه ساله (1391-1382)، مدل­سازی و تخمین زده شد. با استفاده از یک شبکۀ آماربرداری 150×200 تعداد 258 قطعه نمونۀ دائم 10 آری دایره شکل و در مجموع 1895 نمونه برداشت شد. میانگین متغیرهای رویش قطری، سطح مقطع توده، مجموع سطح مقطع بزرگتر از درخت هدف و تعداد در هکتار در داخل قطعۀ نمونه اندازه­گیری شد که به ترتیب برابر 9/30، 8/36، 4/29 و 421 به دست آمد. متغیرهای محیطی از قبیل مقدار انرژی تابشی نور خورشید در فصل رویش، شاخص رطوبت توپوگرافی، ارتفاع بالای نزدیک­ترین نقطۀ زهکشی شده، سرعت باد و متغیرهای زیستی مثل متوسط قطر برابر سینه و سطح مقطع برابر سینه به عنوان متغیرهای ورودی بوده و رویش قطری به عنوان متغیر خروجی شبکۀ عصبی استفاده شد. شبکۀ پرسپترون چند لایه با الگوریتم پس­انتشار خطا به همراه توابع سیگموییدی مورد استفاده قرار گرفت. با توجه به نتایج به ترتیب، شاخص تغییرات قطر برابر سینه (32 درصد)، ترکیب عوامل توپوگرافی و شاخص رطوبت خاک (5/19 درصد) و سطح مقطع برابر سینه (9/16 درصد) تغییرات رویش قطری راش را در سطح قطعۀ نمونه تعریف می­کنند. باد و انرژی تابشی خورشید در فصل رویش نیز مجموعاً 20 درصد تغییرات رویش قطری راش در سطح قطعات نمونه را تعریف می­کنند. شبکۀ عصبی، دقت لازم را برای مدل­سازی رویش قطری با استفاده از عوامل زیست محیطی مؤثر بر آن ارائه داد. همچنین درصد اثرگذاری عوامل محیطی و زیستی حدوداً یکسان بود که می­توان نتیجه گرفت عوامل زیستی و محیطی به صورت تقریباً مساوی رویش قطری راش را کنترل می­کنند.

کلیدواژه‌ها

عنوان مقاله [English]

Analyzing the effect of abiotic and biotic factors on diameter increment of Fagus orientalisl ipsky by artificial neural network in the forests of Mazandaran province

نویسندگان [English]

  • Mahmoud Bayat 1
  • fatemeh gorzin 2
  • majid hasani 3

2 M.Sc. Graduate, Dept. of Forestry and Forest Economics, Faculty of Natural Resources, College of Agriculture and Natural Resources, University of Tehran, Karaj, Iran.

3 M.Sc. Graduate, Research Institute of Forests and Rangelands, Agricultural Research, Education and Extension Organization (AREEO), Tehran, Iran.

چکیده [English]

The diameter and volume growth of forest stands are the basis for determining the annual rate or cut in the planning and management of wood utilization so, forest increment and factors affecting it are one of the most important challenges in the forest. In this study, the impact of biotic and abiotic factors on diameter increment of oriental beech (Fagus orientalis lipsky) in fixed plot-level over a period of 9 years (2003-2012) was modeled by artificial neural network techniques in north forest of Iran. 258 permanent samples were taken by a 150 × 200 inventory grid. Mean of variables such as diameter increment, basal area of stand, basal area of larger trees and number of tree per hectare were measured inside each sample segment which are equal to respectively: 30.9, 36.8, 29.4 and 421. Abiotic factors such as growing-season-cumulated potential solar radiation, seasonal air temperature, topographic wetness index and wind velocity and biotic factors such as diameter at breast height, basal area of larger trees were used as input variables and diameter increment of beech as output variable were used. Multi layer Perceptron network with back propagation algorithm and sigmoid functions were used. The results showed that the changes index of diameter at breast height (32%), Wind and solar energy in the growing season (a total of 20%) the combination of topography and soil wetness index (19.5%) and basal area (16.9 %) explain diameter increment changes in sample plot level. Also, neural networks provided acceptable accuracy for diameter increment modeling using the biotic and abiotic variable affecting on it. Also, the percentage of biotic and abiotic factors was approximately the same, which it can be concluded biotic and abiotic factors control increment of beech the same.

کلیدواژه‌ها [English]

  • "Abiotic and biotic variables"
  • "Artificial intelligence"
  • "Fixed sample plot"
  • "Forest increment"
  • "Natural resources management"
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