作为一种有限的自然资源，磷（P）逐渐成为影响全球可持续发展的新挑战。中国农业对全球可持续磷管理意义重大。在中国集约化的农业生产中，通过根际和土壤磷管理来提高磷的利用效率和作物生产力是很有必要的。之前的研究表明，利用LePA模型（legacy phosphorus assessment model）基于土壤磷管理（恒量监控方法）预测中国未来的磷肥需求量会大大降低。本研究利用LePA模型基于根际和土壤磷综合管理预测了在四种减磷情景下我国各县未来的磷肥需求量。四种情景设置分别为：（1）模拟期间磷肥投入量与2012年相同；（2）低磷县先保持2012年的施磷水平，而高磷县先停施磷肥，直至土壤Olsen-P达目标值，然后施磷量均与作物磷带走量相同；（3）低磷县的土壤Olsen-P达目标值后，各县的施磷量每年降低1 – 7 kg ha^-1，然后每年增加0.1 – 9 kg ha^-1至作物磷带走量；（4）低磷县的磷投入量与2012年相同直至土壤Olsen-P含量升高到目标值，而高磷县的磷投入量先每年降低1 – 7 kg ha^-1，再每年增加0.1 – 9 kg ha^-1，然后与作物磷带走量相同。结果表明，情景4分析的我国在2013 – 2080年期间的磷肥需求总量为6.93亿吨，与农民传统施磷量相比降低了57.5%。与基于土壤管理的磷需求量相比，模拟期间我国磷肥总需求量可进一步降低8.0%。我国平均的土壤Olsen-P含量只需维持在17.2 mg kg^-1即可满足作物高产的需求。我们的研究结果为政府出台可持续磷管理的相关政策提供了坚实的基础。

Chinese farmers are often accused of overusing pesticides that play a crucial role in enhancing crop yield by reducing losses to crop pests. Pesticide overuse has caused a series of negative health and environmental externalities. This paper quantifies the productivity effect and the optimal amount of pesticides in rice, cotton and maize production in China from the economic perspective. Using survey data collected in 2012 and 2013, both Cobb-Douglas and Weibull damage control specifications are used to estimate the production function. Results show that pesticides have statistically significant productivity effect on crop yield. On the condition of Weibull damage control specifications, the marginal products of 1 kg of the active ingredients of pesticides for rice, cotton and maize are 71.06, 22.73 and 98.45 kg, respectively. However, 57, 64 and 17% of the actual amount of pesticides are overused for rice, cotton and maize, respectively. Moreover, the productivity effect of pesticides would be overestimated using Cobb-Douglas specification without incorporating a damage control agent.

Land conversion is considered an effective measure to ensure national food security in China, but little information is available on the quality of low productivity soils, in particular those in acid sulfate soil regions. In our study, acid sulfate paddy soils were divided into soils with high, medium and low levels based on local rice productivity, and 60 soil samples were collected for analysis. Twenty soil variables including physical, chemical and biochemical properties were determined. Those variables that were significantly different between the high, medium and low productivity soils were selected for principal component analysis, and microbial biomass carbon (MBC), total nitrogen (TN), available silicon (ASi), pH and available zinc (AZn) were retained in the minimum data set (MDS). After scoring the MDS variables, they were integrated to calculate a soil quality index (SQI), and the high, medium and low productivity paddy soils received mean SQI scores of 0.95, 0.83 and 0.60, respectively. Low productivity paddy soils showed worse soil quality, and a large discrepancy was observed between the low and high productivity paddy soils. Lower MBC, TN, ASi, pH and available K (AK) were considered as the primary limiting factors. Additionally, all the soil samples collected were rich in available P and AZn, but deficient in AK and ASi. The results suggest that soil AK and ASi deficiencies were the main limiting factors for all the studied acid sulfate paddy soil regions. The application of K and Si on a national basis and other sustainable management approaches are suggested to improve rice productivity, especially for low productivity paddy soils. Our results indicated that there is a large potential for increasing productivity and producing more cereals in acid sulfate paddy soil regions.