Cairns Michael A, Brown Sandra, Helmer Eileen H, Baumgardner Greg A
US Environmental Protection Agency, National Health and Ecological Effects Research Laboratory, Western Ecology Division, 200 SW 35th Street, Corvallis, OR 97333, USA. fax: (541) 754-4799; e-mail:
Department of Forest Science, Forest Science Laboratory, Oregon State University, Corvallis, OR 97331, USA, , , , , , US.
Oecologia. 1997 Jun;111(1):1-11. doi: 10.1007/s004420050201.
Because the world's forests play a major role in regulating nutrient and carbon cycles, there is much interest in estimating their biomass. Estimates of aboveground biomass based on well-established methods are relatively abundant; estimates of root biomass based on standard methods are much less common. The goal of this work was to determine if a reliable method to estimate root biomass density for forests could be developed based on existing data from the literature. The forestry literature containing root biomass measurements was reviewed and summarized and relationships between both root biomass density (Mg ha) and root:shoot ratios (R/S) as dependent variables and various edaphic and climatic independent variables, singly and in combination, were statistically tested. None of the tested independent variables of aboveground biomass density, latitude, temperature, precipitation, temperature:precipitation ratios, tree type, soil texture, and age had important explanatory value for R/S. However, linear regression analysis showed that aboveground biomass density, age, and latitudinal category were the most important predictors of root biomass density, and together explained 84% of the variation. A comparison of root biomass density estimates based on our equations with those based on use of generalized R/S ratios for forests in the United States indicated that our method tended to produce estimates that were about 20% higher.
由于世界森林在调节养分和碳循环方面发挥着重要作用，因此人们对估算其生物量很感兴趣。基于成熟方法的地上生物量估算相对较多；基于标准方法的根系生物量估算则要少得多。这项工作的目标是确定是否可以根据文献中的现有数据开发出一种可靠的方法来估算森林的根系生物量密度。对包含根系生物量测量数据的林业文献进行了综述和总结，并对根系生物量密度（Mg/ha）和根冠比（R/S）作为因变量与各种土壤和气候自变量单独及组合之间的关系进行了统计检验。地上生物量密度、纬度、温度、降水量、温度与降水量之比、树木类型、土壤质地和树龄等经测试的自变量对R/S均无重要解释价值。然而，线性回归分析表明，地上生物量密度、树龄和纬度类别是根系生物量密度最重要的预测因子，共同解释了84%的变异。将基于我们的方程估算的根系生物量密度与基于美国森林广义R/S比率估算的结果进行比较，结果表明我们的方法得出的估算值往往高出约20%。
