Manure amendment can reduce rice yield loss under extreme temperatures

Rice is the primary staple for roughly half of the world’s population, and yields must rise substantially to meet future demand. Climate change is increasing the frequency and intensity of temperature extremes that already negatively affect rice yields. Simultaneously, soil quality degradation and environmental impacts from excessive inorganic fertilizer use challenge sustainable production. Manure amendment is widely recommended to enhance soil fertility and yields, but its role in modulating the impact of extreme temperature on rice yield is unclear. This study tests the hypothesis that long-term manure amendment reduces rice yield losses under extreme temperatures by improving plant nutrition and stress tolerance. The authors address this via a long-term field experiment, a controlled pot experiment probing physiological mechanisms, and a meta-analysis of long-term field studies, with extrapolation to future climates.

Prior work shows excessive inorganic fertilizer causes soil acidification, eutrophication, and groundwater contamination. Recycling manures to cropland is recommended to reduce inorganic fertilizer use and enhance sustainability. Long-term experiments indicate partial substitution (30–70%) of inorganic fertilizers with manure can maintain or increase rice yields in subtropical China. A meta-analysis reported manure amendment increases rice yield and soil organic carbon (SOC), and enhances soil N, P, and K availability. Nutrient availability is known to affect plant responses to abiotic stress including temperature extremes. However, before this study, no experiments had quantified the interaction between manure amendment and extreme temperatures on crop yield.

The study comprised four components: 1) Long-term field experiment: Conducted in a double rice-cropping system in Nanchang, China (28°06′N, 115°09′E), established in 1984 on a ferralic Cambisol (red paddy soil). Treatments: inorganic fertilizers (NPK) versus manure plus inorganic fertilizers (NPKM), with 30% of inorganic fertilizers replaced by Astragalus sinicus (green manure) in early season and fermented swine manure in late season at transplanting. Fertilizer rates (early/late): N 150/180 kg ha−1, P2O5 60/60 kg ha−1, K2O 150/150 kg ha−1. Randomized block design, three replicates, plots separated by concrete walls. Yield measured 1984–2018. Soil properties (SOC, total N, P, K; available N, P, K; bulk density) assessed; paired t-tests for soil comparisons. 2) Pot experiment: Soils collected from each field treatment (0–15 cm). Pots (22 cm diameter, 20 cm height) filled with 4.5 kg air-dried soil; same fertilizer/manure rates as field. Rice (Oryza sativa L. cv. Gan 929) grown outdoors until heading, then subjected for 10 days to controlled temperature regimes in growth chambers: extreme low (daily average ~19.2 °C; min/max 15/25 °C), optimum (~25.3 °C; 21/31 °C), extreme high (~31.5 °C; 27/37 °C). After 10 days, pots returned to field. Grain yield measured at maturity (n=5 pots per treatment). Net foliar photosynthetic rate (flag leaves; LI-6400) and foliar proline concentration (ninhydrin colorimetry) measured at day 10 (n=4 pots per treatment). Two-way ANOVAs (manure, temperature). 3) Meta-analysis: Literature search (Web of Science, CNKI) for long-term (>10 years) field studies in rice with replicated plots comparing NPK versus NPKM (manure plus inorganic fertilizer), with consistent management between treatments; included both partial replacement and same inorganic inputs plus manure. Dataset: 45 studies, 1177 site-year observations. For each study, calculated mean yield and yield losses under extreme temperatures via linear regression of yield on the intensity of temperature extremes (ETI). Soil fertility data (SOC, available N, P, K) also compiled. Effect sizes computed as ln response ratios (lnR = ln(XNPKM/XNPK)); unweighted meta-analysis due to frequently missing variance data; 95% bootstrapped confidence intervals via MetaWin 2.1; reported as percent change after back-transformation. Moderator analyses for cropping system, manure type, soil texture, SOC level, manure N rate, manure N fraction, and whether inorganic fertilizers were replaced. 4) Temperature extreme intensity (ETI) and statistical analyses: Daily air-surface temperature records detrended; for each day, defined baseline range as mean ± 1 SD across multi-year observations. Deviations beyond this range contributed to daily ETI; growing-season ETI computed as the average across days, yielding one ETI per season (0 indicates no extremes). In the field experiment, rice yield loss due to extremes (t ha−1 °C−1) was the absolute slope of yield versus ETI. Three-way ANOVA (manure, season; block as random) for mean yields and yield losses; significance at P < 0.05. SPSS 19.0 used. 5) Extrapolation to future climates: ETI estimated for current decade (2021–2030) and end-century (2091–2100) using multi-model mean air-surface temperatures from four CMIP6 models (CanESM5, CNRM-CM6-1, INM-CM5-0, HadGEM3-GC31-LL). Global rice area from high-resolution cropland maps (5′); transplanting/harvest dates from RiceAtlas. For each pixel, computed ETI and projected yield losses using regressions from meta-analysis (NPK: y = −2.45×ETI + 5.42; NPKM: y = −1.90×ETI + 5.64) to estimate LossNPK and LossNPKM relative to ETI = 0 baselines. Global averages derived across rice-growing pixels.

- Long-term field experiment: NPKM increased mean yield relative to NPK by 5.0% (early season) and 7.2% (late season). Yield decreased with the averaged intensity of temperature extremes (ETI). Manure amendment reduced yield losses due to extreme temperatures by 19.3% (early) and 16.2% (late) compared to NPK. - Pot experiment: Extreme temperatures reduced yields, but reductions were smaller with manure. High temperature decreased yield by 33.2% under NPK vs 24.1% under NPKM; low temperature decreased yield by 19.4% under NPK vs 7.7% under NPKM. - Meta-analysis (45 studies; 1177 site-years): Manure amendment increased rice yield by an average of 7.0%. Yield decreased with ETI across studies, but long-term manure reduced yield losses to extreme temperatures. Regression slopes indicated less sensitivity under NPKM (NPK: y = −2.45×ETI + 5.42; NPKM: y = −1.90×ETI + 5.64). Animal manure and higher manure N inputs conferred stronger reductions in yield loss than green manure and low manure N inputs. - Mechanistic indicators (pot experiment): Extreme temperatures significantly reduced net foliar photosynthetic rates, with smaller reductions under NPKM; extreme temperatures increased foliar proline concentrations, with larger increases under NPKM, indicating enhanced stress responses. - Soil fertility: In the field experiment, NPKM increased SOC by 23.6%, total N by 24.0%, total P by 50.0%, available N by 26.1%, available P by 52.1%, and reduced bulk density; available K unchanged. Meta-analysis showed increases with manure of SOC (+13.8%), available N (+16.0%), available P (+36.6%), and available K (+5.9%). - Extrapolation: Predicted global yield losses due to extreme temperatures average 10.6% (2021–2030) under NPK vs 7.9% with manure; 33.6% (2091–2100) under NPK vs 25.1% with manure. Highest projected losses occur in northern India and the Yangtze River Basin.

The study demonstrates that manure amendment consistently alleviates rice yield losses under extreme temperatures across a long-term field trial, a controlled pot experiment, and a multi-study meta-analysis. Reduced sensitivity of yield to ETI under NPKM is attributed primarily to improved soil fertility and plant nutrition, which maintain higher net photosynthetic rates and enhance physiological stress responses (e.g., greater proline accumulation and activation of stress-responsive pathways). Manure also improves soil structure (lower bulk density), potentially enhancing root growth and resource uptake, and may influence rhizosphere microbiota and introduce humic substances that further bolster stress tolerance. These mechanisms explain how manure mitigates the negative impacts of both heat and cold stress on reproductive-stage rice. The extrapolation indicates substantial potential for manure to reduce climate-change-induced yield losses globally, especially in regions with increasing temperature extremes. Given that adoption of manure remains limited and uneven, integrating manure into nutrient management could strengthen climate resilience and food security while offering environmental co-benefits (reduced reliance on synthetic fertilizers and associated emissions).

Long-term manure amendment increases average rice yields and, critically, reduces yield losses caused by extreme temperatures. Evidence from field, pot, and meta-analytic approaches converges on improved soil fertility and plant stress tolerance as key mechanisms. Scaling manure use in rice systems could reduce projected global yield losses from extreme temperatures (e.g., from 33.6% to 25.1% by century’s end) and contribute to food security and sustainability. Future research should refine projections by accounting for interactions with other global change factors (e.g., CO2, humidity), quantify the relative contributions of specific nutrients, root development, physiological processes, and microbiomes to stress tolerance, and assess how manure type, quality, and N content influence efficacy. Development of logistics, technologies, and policies to support manure collection, processing, and equitable distribution will be vital for large-scale implementation.

- Extrapolations consider only temperature extremes and do not account for other changing factors (e.g., atmospheric CO2, humidity, radiation), whose interactions may alter yield responses and the benefits of manure. - Manure is heterogeneous; effects vary with manure type (animal vs green), N content, and production procedures. This variability introduces uncertainty in generalized projections. - The relative importance of specific mechanisms (nutrient effects, root development, physiological pathways, microbial community changes, humic substances) in conferring temperature-stress tolerance remains unclear. - Meta-analysis was unweighted due to frequent lack of variance reporting in source studies, which may affect precision of effect size estimates.