Eğirdir yöresi doğal karaçam meşcereleri için çap-boy modeli: Kantil regresyon yaklaşımı

Year 2022, , 187 - 195, 29.09.2022

Onur Alkan , Ramazan Ozçelik

https://doi.org/10.18182/tjf.1162582

Abstract

Karaçam (Pinus nigra JF Arnold.) ekonomik ve ekolojik açıdan en önemli ağaç türlerimiz arasında yer almaktadır. Bu nedenle doğal karaçam meşcerelerinin bir taraftan korunması, diğer taraftan da sürdürülebilir yönetimi amacıyla, geleceğe dönük planlama ve stratejilerin oluşturulması için bu meşcerelerin büyüme ve gelişme özelliklerine ilişkin güvenilir bilgilere ihtiyaç duyulmaktadır. Büyüme ve hasılat modellerinin en önemli bileşenlerinden birisi de çap-boy ilişkileridir. Çap ve boy değişkenleri, orman envanteri çalışmalarının da en önemli ölçüm araçlarındadır. Dikili ağaçlarda ağaç boyu ölçümünün göğüs çapı ölçümü kadar kolay olmaması nedeniyle, ağaç boyları orman envanteri çalışmalarında genellikle göğüs çapının bir fonksiyonu olarak tahmin edilmektedir. Bu sebeple, ağaç boyunun doğru ve güvenilir bir şekilde tahmin edilmesi, ormancılık faaliyetleri açısından büyük önem arz etmektedir. Bu çalışmada, Eğirdir yöresi doğal karaçam meşcereleri için Kantil Regresyon (QR) yaklaşımı kullanılarak çap-boy modelleri geliştirilmiştir. Bu amaçla ölçümü yapılan veriler tesadüfi olarak eşit sayıda örnek alan içerecek şekilde iki gruba ayrılmıştır. Diğer modellere göre daha başarılı sonuçlar üretmesi nedeniyle çap-boy modellerinin geliştirilmesinde Chapman-Richards fonksiyonu temel alınmıştır. Çalışma kapsamında üç farklı kantil setini (3, 5 ve 9 katil) temel alan QR modelleri geliştirilmiştir. QR yaklaşımının geleneksel tahmin yöntemlerine göre en önemli üstünlüğü, her örnek alan için ekstra örnek ağaç boyları ile modelin kalibrasyonuna imkân sağlamasıdır. Bu amaçla, QR yöntemi kullanılarak modelin kalibrasyonu amacıyla her örnek alanda tesadüfi olarak seçilen 1-10 arasında değişen sayıda örnek ağaç kullanılarak farklı kalibrasyon alternatifleri test edilmiştir. Çap-boy ilişkilerinin modellenmesi amacıyla 5QR ve 9QR’ye göre daha başarılı sonuçlar üreten ve üç kantil setini temel alan QR’nin yeterli olduğu görülmüştür. Diğer yandan farklı sayıda örnek ağaç verisi kullanılarak yapılan kalibrasyon işleminin boy tahminlerinde önemli iyileşmeler sağladığı, her örnek alanda, beş ağaç kullanılarak yapılacak kalibrasyonun hem modellerin tahmin başarısı hem de örnekleme maliyetleri açısından uygun ve yeterli olduğu görülmüştür.

Keywords

Karaçam, Boy tahmini, Kantil regresyon, Kalibrasyon

Supporting Institution

Türkiye Bilimsel ve Teknolojik Araştırma Kurumu (TÜBİTAK)

Project Number

120R080

Thanks

Bu çalışma, TÜBİTAK tarafından desteklenen 120R080 numaralı “Eğirdir Yöresi Doğal Karaçam Meşcereleri için Çap-Boy Modellerinin Karışık-Etkili Modelleme ve Kantil Regresyon Teknikleri Kullanılarak Geliştirilmesi” projedeki verilerin bir kısmı kullanılarak gerçekleştirilmiştir.

Height-diameter model for natural black pine stands in Eğirdir region: Quantile regression approach

Abstract

Black pine (Pinus nigra JF Arnold.) is one of the most economically and ecologically important tree species in Turkey. In this context, reliable and accurate information about the current status, growth and yield characteristics of these forests is needed for the sustainable management of black pine forests. One of the most important components of growth and yield models is the height-diameter relationships. Diameter and height variables are also the most important measurement tools in forest inventory studies. Since the height of a standing tree cannot be measured as easily as the breast height diameter, tree height is often estimated as a function of diameter in forest inventory studies. For this reason, accurate and reliable estimation of tree height has a great importance for forestry activity. In this study, a height-diameter model was developed for natural black pine stands in Eğirdir region using Quantile Regression (QR) techniques. The measured data were randomly divided into two equal groups. Chapman-Richards height-diameter model was chosen as the base model for both methods since this model has been provided successful results in previous studies. QR models are developed based on three quantile (3, 5 and 9 quantiles) sets in this study. The most important advantage of QR approach over other estimation methods is that QR allows the calibration of the model with extra sample tree heights. For this purpose, different calibration alternatives were tested using a number of trees ranging from 1 to 10 in each sample plot. As a result of the study, it was seen that the 3QR approach performed better than both 5QR and 9QR approaches in terms of describing the height-diameter relationships. In addition, it has been determined that the calibration with five sample trees in each sample plot is appropriate in terms of both the estimation precision of the models and the sampling costs

Keywords

Black pine, Height prediction, Quantile regression, Calibration

Project Number

120R080

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