Project description:Soil labile C and N fractions can change rapidly in response to management practices compared to non-labile fractions. High variability in soil properties in the field, however, results in nonresponse to management practices on these parameters. We evaluated the effects of residue placement (surface application [or simulated no-tillage] and incorporation into the soil [or simulated conventional tillage]) and crop types (spring wheat [Triticum aestivum L.], pea [Pisum sativum L.], and fallow) on crop yields and soil C and N fractions at the 0-20 cm depth within a crop growing season in the greenhouse and the field. Soil C and N fractions were soil organic C (SOC), total N (STN), particulate organic C and N (POC and PON), microbial biomass C and N (MBC and MBN), potential C and N mineralization (PCM and PNM), NH4-N, and NO3-N concentrations. Yields of both wheat and pea varied with residue placement in the greenhouse as well as in the field. In the greenhouse, SOC, PCM, STN, MBN, and NH4-N concentrations were greater in surface placement than incorporation of residue and greater under wheat than pea or fallow. In the field, MBN and NH4-N concentrations were greater in no-tillage than conventional tillage, but the trend reversed for NO3-N. The PNM was greater under pea or fallow than wheat in the greenhouse and the field. Average SOC, POC, MBC, PON, PNM, MBN, and NO3-N concentrations across treatments were higher, but STN, PCM and NH4-N concentrations were lower in the greenhouse than the field. The coefficient of variation for soil parameters ranged from 2.6 to 15.9% in the greenhouse and 8.0 to 36.7% in the field. Although crop yields varied, most soil C and N fractions were greater in surface placement than incorporation of residue and greater under wheat than pea or fallow in the greenhouse than the field within a crop growing season. Short-term management effect on soil C and N fractions were readily obtained with reduced variability under controlled soil and environmental conditions in the greenhouse compared to the field. Changes occurred more in soil labile than non-labile C and N fractions in the greenhouse than the field.
Project description:The industrialization of agriculture has led to an increasing dependence on non-locally sourced agricultural inputs. Hence, shocks in the availability of agricultural inputs can be devastating to food crop production. There is also a pressure to decrease the use of synthetic fertilizers and pesticides in many areas. However, the combined impact of the agricultural input shocks on crop yields has not yet been systematically assessed globally. Here we modelled the effects of agricultural input shocks using a random forest machine learning algorithm. We show that shocks in fertilizers cause the most drastic yield losses. Under the scenario of 50% shock in all studied agricultural inputs, global maize production could decrease up to 26%, and global wheat production up to 21%, impacting particularly the high-yielding 'breadbasket' areas of the world. Our study provides insights into global food system resilience and can be useful for preparing for potential future shocks or agricultural input availability decreases at local and global scales.
Project description:China has been experiencing fine particle (i.e., aerodynamic diameters ≤ 2.5 µm; PM2.5) pollution and acid rain in recent decades, which exert adverse impacts on human health and the ecosystem. Recently, ammonia (i.e., NH3) emission reduction has been proposed as a strategic option to mitigate haze pollution. However, atmospheric NH3 is also closely bound to nitrogen deposition and acid rain, and comprehensive impacts of NH3 emission control are still poorly understood in China. In this study, by integrating a chemical transport model with a high-resolution NH3 emission inventory, we find that NH3 emission abatement can mitigate PM2.5 pollution and nitrogen deposition but would worsen acid rain in China. Quantitatively, a 50% reduction in NH3 emissions achievable by improving agricultural management, along with a targeted emission reduction (15%) for sulfur dioxide and nitrogen oxides, can alleviate PM2.5 pollution by 11-17% primarily by suppressing ammonium nitrate formation. Meanwhile, nitrogen deposition is estimated to decrease by 34%, with the area exceeding the critical load shrinking from 17% to 9% of China's terrestrial land. Nevertheless, this NH3 reduction would significantly aggravate precipitation acidification, with a decrease of as much as 1.0 unit in rainfall pH and a corresponding substantial increase in areas with heavy acid rain. An economic evaluation demonstrates that the worsened acid rain would partly offset the total economic benefit from improved air quality and less nitrogen deposition. After considering the costs of abatement options, we propose a region-specific strategy for multipollutant controls that will benefit human and ecosystem health.
Project description:Europe has experienced a stagnation of some crop yields since the early 1990s as well as statistically significant warming during the growing season. Although it has been argued that these two are causally connected, no previous studies have formally attributed long-term yield trends to a changing climate. Here, we present two statistical tests based on the distinctive spatial pattern of climate change impacts and adaptation, and explore their power under a range of parameter values. We show that statistical power for the identification of climate change impacts is high in many settings, but that power for identifying adaptation is almost always low. Applying these tests to European agriculture, we find evidence that long-term temperature and precipitation trends since 1989 have reduced continent-wide wheat and barley yields by 2.5% and 3.8%, respectively, and have slightly increased maize and sugar beet yields. These averages disguise large heterogeneity across the continent, with regions around the Mediterranean experiencing significant adverse impacts on most crops. This result means that climate trends can account for ? 10% of the stagnation in European wheat and barley yields, with likely explanations for the remainder including changes in agriculture and environmental policies.
Project description:Crop simulation models can be used to estimate impact of current and future climates on crop yields and food security, but require long-term historical daily weather data to obtain robust simulations. In many regions where crops are grown, daily weather data are not available. Alternatively, gridded weather databases (GWD) with complete terrestrial coverage are available, typically derived from: (i) global circulation computer models; (ii) interpolated weather station data; or (iii) remotely sensed surface data from satellites. The present study's objective is to evaluate capacity of GWDs to simulate crop yield potential (Yp) or water-limited yield potential (Yw), which can serve as benchmarks to assess impact of climate change scenarios on crop productivity and land use change. Three GWDs (CRU, NCEP/DOE, and NASA POWER data) were evaluated for their ability to simulate Yp and Yw of rice in China, USA maize, and wheat in Germany. Simulations of Yp and Yw based on recorded daily data from well-maintained weather stations were taken as the control weather data (CWD). Agreement between simulations of Yp or Yw based on CWD and those based on GWD was poor with the latter having strong bias and large root mean square errors (RMSEs) that were 26-72% of absolute mean yield across locations and years. In contrast, simulated Yp or Yw using observed daily weather data from stations in the NOAA database combined with solar radiation from the NASA-POWER database were in much better agreement with Yp and Yw simulated with CWD (i.e. little bias and an RMSE of 12-19% of the absolute mean). We conclude that results from studies that rely on GWD to simulate agricultural productivity in current and future climates are highly uncertain. An alternative approach would impose a climate scenario on location-specific observed daily weather databases combined with an appropriate upscaling method.
Project description:Production systems that feature temporal and spatial integration of crop and livestock enterprises, also known as integrated crop-livestock systems (ICLS), have the potential to intensify production on cultivated lands and foster resilience to the effects of climate change without proportional increases in environmental impacts. Yet, crop production outcomes following livestock grazing across environments and management scenarios remain uncertain and a potential barrier to adoption, as producers worry about the effects of livestock activity on the agronomic quality of their land. To determine likely production outcomes across ICLS and to identify the most important moderating variables governing those outcomes, we performed a meta-analysis of 66 studies comparing crop yields in ICLS to yields in unintegrated controls across 3 continents, 12 crops, and 4 livestock species. We found that annual cash crops in ICLS averaged similar yields (-7% to +2%) to crops in comparable unintegrated systems. The exception was dual-purpose crops (crops managed simultaneously for grazing and grain production), which yielded 20% less on average than single-purpose crops in the studies examined. When dual-purpose cropping systems were excluded from the analysis, crops in ICLS yielded more than in unintegrated systems in loamy soils and achieved equal yields in most other settings, suggesting that areas of intermediate soil texture may represent a "sweet-spot" for ICLS implementation. This meta-analysis represents the first quantitative synthesis of the crop production outcomes of ICLS and demonstrates the need for further investigation into the conditions and management scenarios under which ICLS can be successfully implemented.
Project description:Climate change is expected to cause mass human migration, including immigration across international borders. This study quantitatively examines the linkages among variations in climate, agricultural yields, and people's migration responses by using an instrumental variables approach. Our method allows us to identify the relationship between crop yields and migration without explicitly controlling for all other confounding factors. Using state-level data from Mexico, we find a significant effect of climate-driven changes in crop yields on the rate of emigration to the United States. The estimated semielasticity of emigration with respect to crop yields is approximately -0.2, i.e., a 10% reduction in crop yields would lead an additional 2% of the population to emigrate. We then use the estimated semielasticity to explore the potential magnitude of future emigration. Depending on the warming scenarios used and adaptation levels assumed, with other factors held constant, by approximately the year 2080, climate change is estimated to induce 1.4 to 6.7 million adult Mexicans (or 2% to 10% of the current population aged 15-65 y) to emigrate as a result of declines in agricultural productivity alone. Although the results cannot be mechanically extrapolated to other areas and time periods, our findings are significant from a global perspective given that many regions, especially developing countries, are expected to experience significant declines in agricultural yields as a result of projected warming.
Project description:Globally, around three billion people depend upon solid fuels such as firewood, dry animal dung, crop residues, or coal, and use traditional stoves for cooking and heating purposes. This solid fuel combustion causes indoor air pollution (IAP) and severely impairs health and the environment, especially in developing countries like Pakistan. A number of alternative household energy strategies can be adopted to mitigate IAP, such as using liquefied petroleum gas (LPG), natural gas, biogas, electric stoves, or improved cook stoves (ICS). In this study, we estimate the benefit-cost ratios and net present value of these interventions over a ten-year period in Pakistan. Annual costs include both fixed and operating costs, whereas benefits cover health, productivity gains, time savings, and fuel savings. We find that LPG has the highest benefit-cost ratio, followed by natural gas, while ICS has the lowest benefit-cost ratio. Electric stoves and biogas have moderate benefit-cost ratios that nevertheless exceed one. To maximize the return on cleaner burning technology, the government of Pakistan should consider encouraging the adoption of LPG, piped natural gas, and electric stoves as means to reduce IAP and adopt clean technologies.
Project description:Elevated air temperatures in urban neighborhoods due to the Urban Heat Island effect is a form of heat pollution that causes thermal discomfort, higher energy consumption, and deteriorating public health. Mitigation measures can be expensive, with the need to maximize benefits from limited resources. Here we show that significant mitigation can be achieved through a limited application of reflective surfaces. We use a Computational Fluid Dynamics model to resolve the air temperature within a prototypical neighborhood for different wind directions, building configurations, and partial application of reflective surfaces. While reflective surfaces mitigate heat pollution, their effectiveness relative to cost varies with spatial distribution. Although downstream parts experience the highest heat pollution, applying reflective surfaces to the upstream part has a disproportionately higher benefit relative to cost than applying them downstream.
Project description:After harvesting agricultural crops, the residue can be returned to the soil as mulch. This study performed a meta-analysis of previous research to investigate the effects of crop residue return and other factors on crop yields and water use efficiency (WUE). Overall, the results show that crop residue return increases crop yields by 5.0% relative to crops grown without it. The greatest increases in yield for crops grown with returned residue were associated with average annual temperatures < 10 °C (yield increase = 7.6%), rainfall ≥ 800 mm (9.5%), plowing depth ≥ 20 cm (6.5%), corn crops (8.0%), growth of a single crop per year (10.1%), no irrigation (11.9%), nitrogen (N), and potassium (K) fertilization (20.0%), and low nitrogen application rates of 0-100 kg N ha-1 (10.8%). The effects of crop residue return on crop yields were found to vary according to the following soil properties: organic matter content ≥ 15 g kg-1 (yield increase = 9.4%), available nitrogen content ≥ 100 mg kg-1 (10.3%), and pH ≤ 6.5 (11.2%). The greatest magnitudes of increase in WUE associated with crop residue return were associated with corn (yield increase = 13.7%), medium nitrogen content (100-150 kg ha-1; 23.3%), high soil organic matter (≥ 15 g kg-1; 25.5%) and low air temperatures (< 10 °C; 19.9%). In addition, our results suggest that crop residue return might be most effective in increasing crop yields and WUE in corn crops, crops with a tillage depth ≥ 20 cm, crops grown with moderate nitrogen fertilization (0-150 kg ha-1), growth of a single crop per year, high soil organic matter content (≥ 15 g kg-1), and cold conditions (< 10 °C). Overall, the results of this meta-analysis suggest that crop residue return can increase crop yields and WUE, with the relationship being mainly affected by climatic conditions, plowing depth, fertilization management, crop types, and soil properties.