Neumann Mathias, Godbold Douglas L, Hirano Yasuhiro, Finér Leena
Institute of Silviculture University of Natural Resources and Life Sciences Vienna Austria.
Institute of Forest Ecology University of Natural Resources and Life Sciences Vienna Austria.
J Ecol. 2020 Mar;108(2):496-514. doi: 10.1111/1365-2745.13328. Epub 2020 Jan 10.
Fine roots and above-ground litterfall play a pivotal role in carbon dynamics in forests. Nonetheless, direct estimation of stocks of fine roots remains methodologically challenging. Models are thus widely used to estimate these stocks and help elucidate drivers of fine root growth and turnover, at a range of scales.We updated a database of fine root biomass, necromass and production derived from 454 plots across European forests. We then compared fine root biomass and production to estimates obtained from 19 different models. Typical input variables used for the models included climate, net primary production, foliage and above-ground biomass, leaf area index (LAI), latitude and/or land cover type. We tested whether performance could be improved by fitting new multiple regression models, and explored effects of species composition and sampling method on estimated fine root biomass.Average fine root biomass was 332 g/m, and necromass 379 g/m, for European forests where the average fine root production was 250 g m year. Carbon fraction in fine roots averaged 48.4%, and was 1.5% greater in broadleaved species than conifers.Available models were poor predictors of fine root biomass and production. The best performing models assumed proportionality between above- and below-ground compartments, and used remotely sensed LAI or foliage biomass as key inputs. Model performance was improved by use of multiple regressions, which revealed consistently greater biomass and production in stands dominated by broadleaved species as well as in mixed stands even after accounting for climatic differences. We assessed the potential of existing models to estimate fine root biomass and production in European forests. We show that recalibration reduces by about 40% errors in estimates currently produced by the best available models, and increases three-fold explained variation. Our results underline the quantitative significance of fine roots (live and dead) to the global carbon cycle.
细根和地上凋落物在森林碳动态中起着关键作用。然而，直接估算细根储量在方法上仍具有挑战性。因此，模型被广泛用于估算这些储量，并有助于阐明不同尺度下细根生长和周转的驱动因素。我们更新了一个来自欧洲森林454个样地的细根生物量、死根生物量和生产量的数据库。然后，我们将细根生物量和生产量与19种不同模型得出的估算值进行了比较。这些模型使用的典型输入变量包括气候、净初级生产力、叶量和地上生物量、叶面积指数（LAI）、纬度和/或土地覆盖类型。我们测试了通过拟合新的多元回归模型是否可以提高模型性能，并探讨了物种组成和采样方法对细根生物量估算的影响。欧洲森林的细根平均生物量为332克/平方米，死根生物量为379克/平方米，平均细根年生产量为250克/平方米。细根中的碳含量平均为48.4%，阔叶树种比针叶树种高１.5%。现有模型对细根生物量和生产量的预测效果不佳。表现最佳的模型假定地上和地下部分之间存在比例关系，并将遥感叶面积指数或叶生物量作为关键输入变量。使用多元回归提高了模型性能，多元回归显示，即使考虑了气候差异，阔叶树种占主导的林分以及混交林中的生物量和生产量始终更高。我们评估了现有模型估算欧洲森林细根生物量和生产量的潜力。我们表明，重新校准可将目前最佳可用模型产生的估算误差减少约40%，并将解释变异增加两倍。我们的结果强调了细根（活根和死根）对全球碳循环的定量意义。
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