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Soil CO2 balance and its uncertainty in forestry-drained peatlands in Finland

机译:芬兰森林排水的泥炭地土壤CO2平衡及其不确定性

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To understand the global carbon cycle and the impact of human activity on climate, it is necessary to quantify the net CO2 exchange of ecosystems in different land uses on a large scale. Methods to estimate soil net CO2 exchange (NECO2soil) for drained peatland forests have been largely based on chamber measurements and statistical models. The uncertainty in these methods has not been assessed. Yet, disturbed organic soils are a globally important, potential CO2 source due to their vast carbon storage and its sensitivity to changes in soil moisture.In this study, we estimated the countrywide NECO2soil for the 4.76 million ha of forestry-drained peat soils in Finland. We gathered available litter production and CO2 efflux data and constructed models to be used for the upscaling of NECO2soil from forest inventory data. The contribution of each model and the inventory sampling to the precision of the countrywide estimate was calculated. Also, the sensitivity to possible bias in selected model components was estimated.Compared to the estimated mean NECO2soil, ranging from a source of +20 g m(-2) year(-1) of C to a sink of -40 g m(-2) year(-1) of C, the uncertainty was high. The precision of the estimate (+/- 1 standard deviation) was +/- 20 g m(-2) year(-1) of C. Due to possible bias in the estimated belowground litter input, the overall uncertainty was much higher, around 60 g m(-2) year(-1) of C.The main reason for the high relative uncertainty was NECO2soil being on average close to zero in these boreal forestry-drained peatlands. Forest inventory sample size was large enough and the data for the models were mainly sufficient. To reduce the uncertainty, better understanding of belowground carbon fluxes in order to accurately determine the C input to soil, is crucial.
机译:为了了解全球碳循环以及人类活动对气候的影响,有必要对不同土地利用类型的生态系统的净二氧化碳交换进行大规模量化。估算泥炭地流失森林的土壤净CO2交换量(NECO2土壤)的方法主要基于室内测量和统计模型。这些方法的不确定性尚未评估。然而,受干扰的有机土壤由于其大量的碳存储及其对土壤水分变化的敏感性而成为全球重要的潜在CO2来源。在这项研究中,我们估算了芬兰476万公顷森林排泄的泥炭土壤中的NECO2土壤。 。我们收集了可用的枯枝落叶产量和CO2外排数据,并构建了用于从森林清单数据中放大NECO2土壤规模的模型。计算了每个模型和库存抽样对全国估算精度的贡献。此外,还估算了对选定模型组件中可能存在的偏差的敏感性。与估算的平均NECO2土壤相比,从+20 gm(-2)年(-1)的C碳源到-40 gm(-2 )年(-1),不确定性很高。估算的精度(+/- 1标准偏差)为C的+/- 20 gm(-2)年(-1)。由于估算的地下垫料输入量可能存在偏差,因此总体不确定性要高得多。 60 gm(-2)年(-1)C.相对不确定性高的主要原因是在这些北部森林地带的泥炭地,NECO2土壤平均接近于零。森林清查样本量足够大,模型的数据主要是足够的。为了减少不确定性,对地下碳通量的更好理解以准确确定向土壤中的碳输入至关重要。

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