The long-term persistence of biochar in soil is often predicted by extrapolating mineralization data from short-term laboratory incubations. Single first-order, double first-order, triple first-order and power models have been employed for this purpose, all of which have an inherent assumption that biochar is biodegradable. However, recent insights challenge this assumption by suggesting that a large fraction of biochar is inert. If so, it would make sense to reflect this in the models used, by incorporating an inert carbon (C) pool. We hypothesized that such inert pool models would fit better to incubation data than existing models and give more reliable long-term predictions. We evaluated this by fitting the models to data from a recently compiled extensive dataset of biochar incubations. The inclusion of an inert pool enhanced the model fits over first-order models in most cases. However, inert pool models overestimated biochar persistence compared to the measured outcomes. By contrast, the double first-order model, which has been the most widely used to date, underestimated biochar persistence even in the short term. The power model in general outperformed all other models and gave the most reliable predictions, although it was sensitive to increasing or fluctuating mineralization rates in the datasets.

中文翻译：

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惰性池模型能否改善对生物炭在土壤中长期持久性的预测？


生物炭在土壤中的长期持久性通常是通过推断短期实验室孵化的矿化数据来预测的。为此，已采用单一阶、双一阶、三重一阶和幂模型，所有这些模型都有一个固有的假设，即生物炭是可生物降解的。然而，最近的见解挑战了这一假设，表明大部分生物炭是惰性的。如果是这样，那么通过加入惰性碳 （C） 池来反映这一点在所使用的模型中是有意义的。我们假设这种惰性池模型比现有模型更适合孵化数据，并给出更可靠的长期预测。我们通过将模型与最近编译的广泛生物炭孵化数据集中的数据拟合来评估这一点。在大多数情况下，惰性池的加入增强了模型拟合度，而不是一阶模型。然而，与测量结果相比，惰性池模型高估了生物炭持久性。相比之下，迄今为止使用最广泛的双一阶模型即使在短期内也低估了生物炭的持久性。幂模型总体上优于所有其他模型，并给出了最可靠的预测，尽管它对数据集中矿化速率的增加或波动很敏感。