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Journals / Tekirdağ Ziraat Fakültesi Dergisi / 2026 / Cilt: 23 Sayı: 1

Assessing the Correlation among Soil Quality, Tree Species, and Productivity in forest ecosystems using SMAF Method

SMAF Yöntemi Kullanılarak Orman Ekosistemlerinde Toprak Kalitesi, Ağaç Türleri ve Verimlilik Arasındaki Korelasyonun Değerlendirilmesi

Ahmet Reis(Kahramanmaraş Sütçü İmam Üniversitesi Orman Mühendisliği Orman Fakültesi)0000-0003-3247-4174
Nurullah Acir(KIRŞEHİR AHİ EVRAN ÜNİVERSİTESİ, ZİRAAT FAKÜLTESİ)0000-0001-7591-0496
Turgay Dindaroğlu(KARADENİZ TEKNİK ÜNİVERSİTESİ, ORMAN FAKÜLTESİ)0000-0003-2165-8138
Pages
32–49
Publication Date
2026-01-07
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AI Summary & Key Takeaways

AI Insight
⚡ TL;DR(Too Long; Didn't Read)

Results showed that soil quality was lowest in black pine stands (69.42%) and the highest in oak stands (77.31%).

📌 3 Key Takeaways

🎯
Objective & Hypothesis:Ensuring soil quality and sustainability is of vital importance in combating global climate change and desertification.
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Key Findings & Data:Evaluating soil quality accurately is essential, and the Soil Management Assessment Framework (SMAF) is a method that uses soil indicators to assess soil properties comprehensively.
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Conclusion & Impact:Results showed that soil quality was lowest in black pine stands (69.42%) and the highest in oak stands (77.31%).
🔬Design:Araştırma Makalesi
📍Scope:Comprehensive Sample
⚙️Variables:Toprak kalitesi · SMAF · Bonitet sınıfları

Abstract

Ensuring soil quality and sustainability is of vital importance in combating global climate change and desertification. Factors such as weakening of vegetation, soil erosion, compaction, and degradation reduce soil fertility, thus impacting soil quality. Evaluating soil quality accurately is essential, and the Soil Management Assessment Framework (SMAF) is a method that uses soil indicators to assess soil properties comprehensively. This study aimed to evaluate the relationship among tree species, bonitet classes, and soil quality in forest ecosystems at the watershed scale using the SMAF method. The research took place in the Karasu Watershed in Akifiye, Andırın district of Kahramanmaraş province. Soil indicators were selected from the physical and chemical properties of the soil. Soil indicators such as aggregate stability, water-filled pore volume, bulk density, carbon content, nutrient levels, pH, and electrical conductivity were used to determine soil quality indices in forest stands. Soil quality indices were determined and statistically interpreted by applying the SMAF method between tree species and bonitet classes in forest lands. Results showed that soil quality was lowest in black pine stands (69.42%) and the highest in oak stands (77.31%). Leafy stands had statistically higher soil quality. Soil quality indices ranged from 72.54 to 74.75 across bonitet classes, which are indicators of productivity (bonitet) in forest stands. No significant differences were found between bonitet classes and soil quality scores in karst forest ecosystems due to their karstic characteristics. Although soil quality may be high in karst areas, shallow soil depth limits plant growth. Therefore, a high soil quality index in karst areas can correspond to a low bonitet class. The negative effects of production activities and silvicultural interventions in forest ecosystems on soil quality can be eliminated by activities such as soil tillage. Implementing management strategies that prioritize soil protection and improvement in forest ecosystems with natural plant cover will enhance soil functionality and ensure long-term soil quality sustainability.

Özet

Toprak kalitesinin ve sürdürülebilirliğinin sağlanması, küresel iklim değişikliği ve çölleşmeyle mücadelede hayati öneme sahiptir. Bitki örtüsünün zayıflaması, toprak erozyonu, sıkışma ve bozulma gibi faktörler toprak verimliliğini azaltır ve böylece toprak kalitesini etkiler. Toprak kalitesini doğru bir şekilde değerlendirmek esastır ve Toprak Yönetimi Değerlendirme Çerçevesi (SMAF), toprak özelliklerini kapsamlı bir şekilde değerlendirmek için toprak göstergelerini kullanan bir yöntemdir. Bu çalışma, SMAF yöntemini kullanarak havza ölçeğinde orman ekosistemlerindeki ağaç türleri, bonitet sınıfları ve toprak kalitesi arasındaki ilişkiyi değerlendirmeyi amaçlamaktadır. Araştırma, Kahramanmaraş ili Andırın ilçesi Akifiye'deki Karasu Havzası'nda yapılmıştır. Toprağın fiziksel ve kimyasal özelliklerinden toprak göstergeleri seçilmiştir. Agregat kararlılığı, suyla dolu gözenek hacmi, hacim ağırlığı, karbon içeriği, besin seviyeleri, pH ve elektriksel iletkenlik gibi toprak göstergeleri, ormanlık alanlardaki toprak kalitesi endekslerini belirlemek için kullanılmıştır. Orman arazilerinde ağaç türü ve bonitet sınıfları arasında SMAF yöntemi uygulanarak toprak kalitesi endeksleri belirlenmiş ve istatistiki olarak yorumlanmıştır. Sonuçlar, toprak kalitesinin karaçam ormanlarında en düşük (%69.42) ve meşe ormanlarında en yüksek (%77.31) olduğunu göstermiştir. Yapraklı ormanların toprak kalitesi istatistiksel olarak daha yüksektir. Toprak kalitesi endeksleri, orman alanlarındaki üretkenliğin (bonitet) göstergesi olan bonitet sınıfları arasında 72.54 ile 74.75 arasında değişmektedir. Karstik özellikleri nedeniyle karst orman ekosistemlerinde bonitet sınıfları ve toprak kalitesi skorları arasında önemli bir fark bulunamamıştır. Toprak kalitesi karst alanlarında yüksek olsa da, sığ toprak derinliği bitki büyümesini sınırlamaktadır. Bu nedenle, karst alanlarında yüksek bir toprak kalitesi endeksi düşük bir bonitet sınıfına karşılık gelebilir. Orman ekosistemlerinde üretim çalışmaları ve silvikültürel müdahalelerin toprak kalitesindeki negatif etkisi toprak işleme gibi faaliyetlerle ortadan kaldırılabilir. Doğal bitki örtüsüne sahip orman ekosistemlerinde toprak koruma ve iyileştirmeyi önceliklendiren yönetim stratejilerinin uygulanması, toprak işlevselliğini artıracak ve uzun vadeli toprak kalitesi sürdürülebilirliğini sağlayacaktır.

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Cite This Article

Reis, A., Acir, N., Dindaroğlu, T. (2026). Assessing the Correlation among Soil Quality, Tree Species, and Productivity in forest ecosystems using SMAF Method. Tekirdağ Ziraat Fakültesi Dergisi, Cilt: 23 Sayı: 1, 32–49. https://doi.org/10.33462/jotaf.1527232

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