Abstract Diversification of cropping is perceived as a strategy to simultaneously achieve high productivity and maintain environmental sustainability. In southern Africa, however, due to a lack of medium to long-term field trials, there is missing quantitative information. Utilising the capability of agro-ecosystem models to quantify the interactions of crop productivity with management and environmental variables, the APSIM model was evaluated against six and an eight-year field trial datasets comprised of different crop rotations and fertiliser rates under two contrasting agro-ecological conditions in South Africa (clay soil with a mean rainfall of 871 mm versus a sandy soil with a 570 mm rainfall). Model output was compared to observed grain yield, aboveground dry matter, soil organic carbon (SOC), and mineral nitrogen (Nmin) dynamics. APSIM was able to reproduce the observed grain yield dynamics fairly well as indicated by a Wilmott index of agreement of 0.90. Prediction accuracy, as indicated by the absolute model error across all crops, however, only reached 39%. Simulated Nmin and SOC dynamics showed similar patterns to the observations. Subsequently, the model was applied in a ten-year simulation experiment with rotation treatments (14 rotations, respectively intercropping systems, including a maize monoculture control), fertiliser levels (zero and 70 kg N ha−1), and residue management (retained and removed) for the two sites. For low input systems, such as smallholder farms, residue management and legume integration are of the utmost importance to maintain SOC and more pronounced Nmin levels, which, for the sandy soil, resulted in an average maize yield increase of up to 1000 kg ha−1. Maize monoculture treatments with residues removed reduced SOC moderately by 0.04–0.08 %, while yields declined strongly (>1000 kg ha−1) over the simulated period of ten years. In commercial, fertilised cropping systems, allocating land to cultivate crops other than maize reduced the simulated total yield performance. This diversification disadvantage has to be considered against the benefits of increased SOC and yields in the medium-term, i.e. a period of ten years. For the commercial systems, maize intercropped with delayed sown oats or cowpea appeared promising.

中文翻译：

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模拟种植系统多样化对南部非洲土壤肥力和作物生产力的中期影响

摘要 种植多样化被认为是一种同时实现高生产力和保持环境可持续性的策略。然而，在南部非洲，由于缺乏中长期田间试验，缺少定量信息。利用农业生态系统模型的能力来量化作物生产力与管理和环境变量之间的相互作用，根据 6 年和 8 年的田间试验数据集对 APSIM 模型进行了评估，这些数据集包括两种不同的农业生态系统下的不同作物轮作和施肥率。南非的条件（粘土平均降雨量为 871 毫米，而沙土平均降雨量为 570 毫米）。将模型输出与观察到的谷物产量、地上干物质、土壤有机碳 (SOC) 和矿物氮 (Nmin) 动态进行比较。APSIM 能够很好地再现观察到的谷物产量动态，如威尔莫特一致性指数 0.90 所示。然而，如所有作物的绝对模型误差所示，预测准确度仅达到 39%。模拟的 Nmin 和 SOC 动态显示出与观察结果相似的模式。随后，将该模型应用于为期十年的模拟试验，包括轮作处理（14 轮轮作，分别为间作系统，包括玉米单一栽培控制）、肥料水平（零和 70 kg N ha-1）和残留管理（保留和删除）两个站点。对于小农农场等低投入系统，残留物管理和豆科植物整合对于维持 SOC 和更显着的 Nmin 水平至关重要，对于沙质土壤，导致平均玉米产量增加高达 1000 kg ha-1。去除残留物的玉米单一栽培处理使 SOC 适度降低 0.04–0.08%，而在十年的模拟期内，产量大幅下降（>1000 kg ha-1）。在商业化施肥种植系统中，分配土地种植玉米以外的作物会降低模拟的总产量表现。必须将这种多样化的劣势与中期（即十年）增加 SOC 和产量的好处相比较。对于商业系统，玉米与延迟播种的燕麦或豇豆间作似乎很有希望。施肥耕作系统，分配土地种植玉米以外的作物会降低模拟的总产量表现。必须将这种多样化的劣势与中期（即十年）增加 SOC 和产量的好处相比较。对于商业系统，玉米与延迟播种的燕麦或豇豆间作似乎很有希望。施肥耕作系统，分配土地种植玉米以外的作物会降低模拟的总产量表现。必须将这种多样化的劣势与中期（即十年）增加 SOC 和产量的好处相比较。对于商业系统，玉米与延迟播种的燕麦或豇豆间作似乎很有希望。