کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
6541722 1421340 2018 9 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Predicting tree height from tree diameter and dominant height using mixed-effects and quantile regression models for two species in Turkey
ترجمه فارسی عنوان
پیش بینی ارتفاع درخت از قطر درخت و ارتفاع غالب با استفاده از اثرات ترکیبی و مدل رگرسیون کیفی برای دو گونه در ترکیه
کلمات کلیدی
چپمن ریچاردز، کالیبراسیون، کاج براتیان، سدر تختخواب تلاش نمونه برداری،
موضوعات مرتبط
علوم زیستی و بیوفناوری علوم کشاورزی و بیولوژیک بوم شناسی، تکامل، رفتار و سامانه شناسی
چکیده انگلیسی
Height-diameter models were developed for Brutian pine (Pinus brutia Ten.) and Taurus cedar (Cedrus libani A. Rich.) in Turkey. A modified Chapman-Richards model that includes dominant height was used to predict tree height from diameter. Using the twofold evaluation scheme, five alternative modeling approaches were evaluated: (1) fixed-effects model, (2) calibrated fixed-effects model, (3) calibrated mixed-effects model, (4) three-quantile regression method, and (5) five-quantile regression method. Parameters of fixed-effects, mixed-effects and quantile regression models were calibrated by use of a subset of height measurements, ranging from 1 to 10 sample trees per plot. Evaluation statistics show that both quantile regression models produced similar results, and that the mixed-effects model approach yielded the best results in predicting tree heights. Model performance improved with increasing sample size; but gains in performance generally increased at a decreasing rate. A sample size of four trees per plot appears to be a good compromise between sampling cost and predictive accuracy and precision.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Forest Ecology and Management - Volumes 419–420, 1 July 2018, Pages 240-248
نویسندگان
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