Modeling denitrification nitrogen losses in China's rice fields based on multiscale field-experiment constraints.

Denitrification plays a critical role in soil nitrogen (N) cycling, affecting N availability in agroecosystems. However, the challenges in direct measurement of denitrification products (NO, N2 O, and N2 ) hinder our understanding of denitrification N losses patterns across the spatial scale. To address this gap, we constructed a data-model fusion method to map the county-scale denitrification N losses from China's rice fields over the past decade. The estimated denitrification N losses as a percentage of N application from 2009 to 2018 were 11.8 ± 4.0% for single rice, 12.4 ± 3.7% for early rice, and 11.6 ± 3.1% for late rice. The model results showed that the spatial heterogeneity of denitrification N losses is primarily driven by edaphic and climatic factors rather than by management practices. In particular, diffusion and production rates emerged as key contributors to the variation of denitrification N losses. These findings humanize a 38.9 ± 4.8 kg N ha-1 N loss by denitrification and challenge the common hypothesis that substrate availability drives the pattern of N losses by denitrification in rice fields.

Extreme rainfall reduces one-twelfth of China's rice yield over the last two decades.

Extreme climate events constitute a major risk to global food production. Among these, extreme rainfall is often dismissed from historical analyses and future projections, the impacts and mechanisms of which remain poorly understood. Here we used long-term nationwide observations and multi-level rainfall manipulative experiments to explore the magnitude and mechanisms of extreme rainfall impacts on rice yield in China. We find that rice yield reductions due to extreme rainfall were comparable to those induced by extreme heat over the last two decades, reaching 7.6 ± 0.9% (one standard error) according to nationwide observations and 8.1 ± 1.1% according to the crop model incorporating the mechanisms revealed from manipulative experiments. Extreme rainfall reduces rice yield mainly by limiting nitrogen availability for tillering that lowers per-area effective panicles and by exerting physical disturbance on pollination that declines per-panicle filled grains. Considering these mechanisms, we projected ~8% additional yield reduction due to extreme rainfall under warmer climate by the end of the century. These findings demonstrate that it is critical to account for extreme rainfall in food security assessments.

Decline in nitrogen concentrations of eutrophic Lake Dianchi associated with policy interventions during 2002-2018.

Excessive nutrient discharges have resulted in pervasive water pollution and aquatic eutrophication. China has made massive efforts to improve water quality since 2000. However, how long-term policy interventions govern external and internal fluxes as well as nitrogen (N) concentrations is not well known. Here we examined the historical N concentration change and its key drivers in eutrophic Lake Dianchi (southwest China) over the period 2002-2018, based on monthly observations of water quality and external N fluxes, local surveys of mitigation measures, and process-based model simulations of internal N fluxes. Our data indicated that N concentrations peaked at 3.0 mg L-1 in 2007-2010 but afterwards declined down to 1.2 mg L-1 in 2018. Compared with 2010, the decline in lake N concentrations was attributed to reduced riverine N inflow decreasing by 0.20 g N m-3 month-1 and the water-sediment exchange flux decreasing by 0.07 g N m-3 month-1 from 2010 to 2018. Adoptions of wastewater treatment, pollution interception, and transboundary water transfer dominated the changes in external and internal fluxes of N and thereby the decline of lake N concentrations. These findings underscore the priority of reducing external discharge for historical lake water quality improvement and the need of enhancing internal N removal for future lake ecosystem restoration.

Increased extreme hourly precipitation over China's rice paddies from 1961 to 2012.

Rice yield have been affected by the increased extreme precipitation events in recent decades. Yet, the spatio-temporal patterns of extreme precipitation by rice type and phenology remain elusive. Here, we investigate the characteristics of four extreme precipitation indices across China's rice paddy and their potential association with crop yields, by using hourly precipitation data from 1,215 stations and rice phenology observations from 45 sub-regions. The data indicate that hourly extreme precipitation have significantly increased in 1961-2012 for single rice and early rice in China but not for late rice. Rice were mainly exposed to extreme precipitation from transplantation to flowering stages. The frequency and proportion of extreme precipitation were significantly increased by 2.0-4.7% and 2.3-2.9% per decade, respectively, mainly in south China and Yangtze River Basin. The precipitation intensity and maximum hourly precipitation were increased by 0.7-1.1% and 0.9-2.8% per decade, respectively, mainly in central China and southeast coastal area. These extreme precipitation indices played a role as important as accumulated precipitation and mean temperature on the interannual variability of rice yields, regardless of rice types. Our results also highlight the urgencies to uncover the underlying mechanisms of extreme precipitation on rice growth, which in turn strengthens the predictability of crop models.