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Modeling the productivity of commercial Lactarius mushrooms: A case study in the Kizilcasu planning unit, Turkey
Author(s) -
Mumcu Kucuker Derya,
Baskent Emin Zeki
Publication year - 2019
Publication title -
natural resource modeling
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.28
H-Index - 32
eISSN - 1939-7445
pISSN - 0890-8575
DOI - 10.1111/nrm.12178
Subject(s) - mushroom , lactarius , productivity , stock (firearms) , forest management , agroforestry , forestry , environmental science , yield (engineering) , agricultural engineering , geography , biology , botany , engineering , economics , materials science , archaeology , metallurgy , macroeconomics
Empirical models for mushroom productivity are essential tools for analyzing trade‐offs among multiple objectives when developing and implementing integrated forest management plans. In this study, data measured in 30 permanent plots from a 4‐year period of mushroom production were used to predict mushroom productivity. The fresh weights of Lactarius deliciosus and L. salmonicolor mushrooms were recorded in each sample plot. Owing to the hierarchical structure of the data obtained, equations were developed to produce mixed models using stand and topographic variables. The results showed that increasing slopes increased annual yield in northerly aspects, yet decreased the annual yield in southerly aspects. Besides, the productivity was negatively influenced by height, age and crown closure, and positively influenced by mean stand diameter, growing stock and elevation alone. However, the combined effects of age and diameter and the combined effects of growing stock and height separately showed a negative trend on mushroom yield. Recommendation for Resource Managers Productivity models were developed as important tools in developing nonwood forest products integrated forest management plans. The models show that annual yield of Lactarius mushroom is significantly influenced by certain stand and topographic variables. Use of these models is critical for analyzing trade‐offs among various forest values such as wood and nonwood forest products. The models could lead to optimization of the production and conservation of fungal resources and allow forest managers and field foresters to forecast mushroom production and manage forest interventions affecting mushroom production.

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