An improved method for measuring the production, mortality and decomposition of extramatrical mycelia of ectomycorrhizal fungi in forests
An improved method for measuring the production, mortality and decomposition of extramatrical mycelia of ectomycorrhizal fungi in forests
复制标题
测量森林外生菌根真菌体外菌丝体产生、死亡率和分解的改进方法
DOI：
10.1016/j.soilbio.2017.10.035
复制
发表时间：
2018
影响因子：
9.7
通讯作者：
J. King
中科院分区：
文献类型：
--
作者：
Xuefeng Li;J. King
尽管外生菌根真菌在森林土壤碳循环中具有重要作用，但其基质外菌丝体（EMM）的产量和死亡率却很难量化。生长袋/岩心法是最广泛使用的方法，但不能准确评估EMM产量和死亡率的时间变化，导致年度估计值存在很大的不确定性。提出了一种改进的方法，使用两个数学模型（生物标志物和代数模型），以量化EMM生产，死亡率和分解在不同的时间段整合EMM分解动力学与向内生长的核心/袋数据。在生物标志物模型中，假设EMM生物量和EMM总质量（坏死物质和生物量的总和）通过使用化学生物标志物作为代理是已知的。在代数模型中，只有总质量是已知的，生物量是使用代数方法计算的。火炬松种植园的模型应用表明，使用生物标志物模型时，三个时间段的月平均EMM产量、死亡率和分解估计值分别为10.1 - 16.0 kg ha−1、6.6-15.0 kg ha−1和1.4-6.1 kg ha−1，而这些估计值为24.8 - 35.7 kg ha−1，在使用Algestra模型时，分别为15.5-22.8千克公顷-1和5.7-9.8千克公顷-1，表明评估时间变化的重要性。模型验证表明，与长期孵育（184天与322天）相比，短期EMM估计值更可靠。我们的方法可以通过准确评估森林中EMM产量、死亡率和分解率的时间变化来提高EMM估计。
The production and mortality of extramatrical mycelia (EMM) of ectomycorrhizal fungi are poorly quantified despite their importance in soil carbon cycling in forests. Ingrowth bag/core methods are the most widely used but can not accurately assess temporal changes in EMM production and mortality, resulting in great uncertainty in annual estimates. A modified method using two mathematical models (Biomarker and Algebraic models) is proposed to quantify EMM production, mortality and decomposition over differing time periods by integrating EMM decomposition dynamics with ingrowth core/bag data. In the Biomarker model, EMM biomass and EMM total mass (sum of necromass and biomass) are assumed to be known by using chemical biomarkers as proxies. In the Algebraic model, only the total mass is known and the biomass is calculated using an algebraic method. Model application in a loblolly pine plantation showed that mean monthly EMM production, mortality and decomposition estimates among three time periods ranged from 10.1 to 16.0 kg ha−1, 6.6–15.0 kg ha−1, and 1.4–6.1 kg ha−1, respectively, when using the Biomarker model, while these estimates ranged from 24.8 to 35.7 kg ha−1, 15.5–22.8 kg ha−1, and 5.7–9.8 kg ha−1, respectively, when using the Algebraic model, demonstrating the importance of assessing temporal changes. Model validation indicated that EMM estimates were more reliable for short-term compared to long-term incubation (184 vs. 322 days). Our method could improve EMM estimation by accurately assessing temporal changes in EMM production, mortality and decomposition in forests.