Browsing by Author "Jian, Jinshi"

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    Conservation management decreases surface runoff and soil erosion
    Du, Xuan; Jian, Jinshi; Du, Can; Stewart, Ryan D. (Keai Publishing Ltd, 2022-06)
    Conservation management practices - including agroforestry, cover cropping, no-till, reduced tillage, and residue return - have been applied for decades to control surface runoff and soil erosion, yet results have not been integrated and evaluated across cropping systems. In this study we collected data comparing agricultural production with and without conservation management strategies. We used a bootstrap resampling analysis to explore interactions between practice type, soil texture, surface runoff, and soil erosion. We then used a correlation analysis to relate changes in surface runoff and soil erosion to 13 other soil health and agronomic indicators, including soil organic carbon, soil aggregation, infiltration, porosity, subsurface leaching, and cash crop yield. Across all conservation management practices, surface runoff and erosion had respective mean decreases of 67% and 80% compared with controls. Use of cover cropping provided the largest decreases in erosion and surface runoff, thus emphasizing the importance of maintaining continuous vegetative cover on soils. Coarse- and medium-textured soils had greater decreases in both erosion and runoff than fine-textured soils. Changes in surface runoff and soil erosion under conservation management were highly correlated with soil organic carbon, aggregation, porosity, infiltration, leaching, and yield, showing that conservation practices help drive important interactions between these different facets of soil health. This study offers the first large-scale comparison of how different conservation agriculture practices reduce surface runoff and soil erosion, and at the same time provides new insight into how these interactions influence the improvement or loss of soil health. (C) 2021 International Research and Training Center on Erosion and Sedimentation, China Water and Power Press, and China Institute of Water Resources and Hydropower Research. Publishing services by Elsevier B.V. on behalf of KeAi Communications Co. Ltd.
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    A database for global soil health assessment
    Jian, Jinshi; Du, Xuan; Stewart, Ryan D. (2020-01-13)
    Field studies have been performed for decades to analyze effects of different management practices on agricultural soils and crop yields, but these data have never been combined together in a way that can inform current and future cropland management. Here, we collected, extracted, and integrated a database of soil health measurements conducted in the field from sites across the globe. The database, named SoilHealthDB, currently focuses on four main conservation management methods: cover crops, no-tillage, agro-forestry systems, and organic farming. These studies represent 354 geographic sites (i.e., locations with unique latitudes and longitudes) in 42 countries around the world. The SoilHealthDB includes 42 soil health indicators and 46 background indicators that describe factors such as climate, elevation, and soil type. A primary goal of this effort is to enable the research community to perform comprehensive analyses, e.g., meta-analyses, of soil health changes related to cropland conservation management. The database also provides a common framework for sharing soil health, and the scientific research community is encouraged to contribute their own measurements.
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    Future Global Soil Respiration Rates Will Swell Despite Regional Decreases in Temperature Sensitivity Caused by Rising Temperature
    Jian, Jinshi; Steele, Meredith K.; Day, Susan D.; Thomas, R. Quinn (American Geophysical Union, 2018)
    Between 1960 and 2014, the global soil respiration (RSG) flux increased at a rate of 0.05 Pg C year⁻¹; however, future increase is uncertain due to variations in projected temperature and regional heterogeneity. Regional differences in the sensitivity of soil respiration (RS) to temperature may alter the overall increase in rates of RS because the RS rates of some regions may decelerate while others continue to rise. Using monthly global RS data, we modeled the relationship between RS and temperature for the globe and eight climate regions and estimated RSG between 1961 and 2100 using historical (1961–2014) and future (2015–2100) temperature data [Representative Concentration Pathways (RCP2.6 and RCP8.5)]. Importantly, our approach allowed for estimation of regional sensitivity, where respiration rates may peak or decline as temperature rises. Estimated historical RSG increase (0.05 Pg C year⁻¹) was similar to the RSG increase of previous estimates. However, under the RCP8.5 scenario, which estimates approximately 3 °C of warming globally, the forecasted acceleration of RSG increased to an average of 0.12 Pg C year⁻¹. Under RCP8.5, the temperature sensitivity of RS declined in the arid, winter-dry temperate, and tropic. These regional declines were offset by increased RS sensitivity and fluxes from the boreal and polar regions. In contrast, under RCP2.6 RSG decelerated slightly from current rates. If rising greenhouse gas emission remains unmitigated, future increases in RSG will be much faster than current and historical rates, thereby possibly enhancing future losses of soil carbon and contributing to positive feedback loops of climate change.
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    Global soil respiration: interaction with macroscale environmental variables and response to climate change
    Jian, Jinshi (Virginia Tech, 2018-02-05)
    The response of global soil respiration (Rs) to climate change determines how long the land can continue acting as a carbon sink in the future. This dissertation research identifies how temporal and spatial variation in environmental factors affects global scale Rs modeling and predictions of future Rs under global warming. Chapter 1 describes the recommend time range for measuring Rs across differing climates, biomes, and seasons and found that the best time for measuring the daily mean Rs is 10:00 am in almost all climates and biomes. Chapter 2 describes commonly used surrogates in Rs modeling and shows that air temperature and soil temperature are highly correlated and that they explain similar amounts of Rs variation; however, average monthly precipitation between 1961 and 2014, rather than monthly precipitation for a specific year, is a better predictor in global Rs modeling. Chapter 3 quantifies the uncertainty generated by four different assumptions of global Rs models. Results demonstrate that the time-scale of the data, among other sources, creates a substantial difference in global estimates, where the estimate of global annual Rs based on monthly Rs data (70.85 to 80.99 Pg C yr-1) is substantially lower than the current benchmark for land models (98 Pg C yr-1). Chapter 4 simulates future global Rs rates based on two temperature scenarios and demonstrates that temperature sensitivity of Rs will decline in warm climates where the level of global warming will reach 3°C by 2100 relative to current air temperature; however, these regional decelerations will be offset by large Rs accelerations in the boreal and polar regions. Chapter 5 compares CO2 fluxes from turfgrass and wooded areas of five parks in Blacksburg, VA and tests the ability of the Denitrification-Decomposition model to estimate soil temperature, moisture and CO2 flux across the seasons. Cumulatively, this work provides new insights into the current and future spatial and temporal heterogeneity of Rs and its relationship with environmental factors, as well as key insights in upscaling methodology that will help to constrain global Rs estimates and predict how global Rs will respond to global warming in the future.
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    Historically inconsistent productivity and respiration fluxes in the global terrestrial carbon cycle
    Jian, Jinshi; Bailey, Vanessa; Dorheim, Kalyn; Konings, Alexandra G.; Hao, Dalei; Shiklomanov, Alexey N.; Snyder, Abigail; Steele, Meredith; Teramoto, Munemasa; Vargas, Rodrigo; Bond-Lamberty, Ben (Springer Nature, 2022-04-01)
    The terrestrial carbon cycle is a major source of uncertainty in climate projections. Its dominant fluxes, gross primary productivity (GPP), and respiration (in particular soil respiration, RS), are typically estimated from independent satellite-driven models and upscaled in situ measurements, respectively. We combine carbon-cycle flux estimates and partitioning coefficients to show that historical estimates of global GPP and RS are irreconcilable. When we estimate GPP based on RS measurements and some assumptions about RS:GPP ratios, we found the resulted global GPP values (bootstrap mean 149+29−23 Pg C yr−1) are significantly higher than most GPP estimates reported in the literature (113+18−18 Pg C yr−1). Similarly, historical GPP estimates imply a soil respiration flux (RsGPP, bootstrap mean of 68+10−8 Pg C yr−1) statistically inconsistent with most published RS values (87+9−8 Pg C yr−1), although recent, higher, GPP estimates are narrowing this gap. Furthermore, global RS:GPP ratios are inconsistent with spatial averages of this ratio calculated from individual sites as well as CMIP6 model results. This discrepancy has implications for our understanding of carbon turnover times and the terrestrial sensitivity to climate change. Future efforts should reconcile the discrepancies associated with calculations for GPP and Rs to improve estimates of the global carbon budget.
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    Impact of Land Use/Cover Changes on Soil Erosion by Wind and Water from 2000 to 2018 in the Qaidam Basin
    Cao, Xue; Cheng, Yuzhuo; Jiao, Juying; Jian, Jinshi; Bai, Leichao; Li, Jianjun; Ma, Xiaowu (MDPI, 2023-09-30)
    Assessing the impact of land use and land cover change (LUCC) on soil erosion by wind and water is crucial for improving regional ecosystem services and sustainable development. In this study, the Revised Wind Erosion Equation (RWEQ) and Revised Universal Soil Loss Equation (RUSLE) were used to reveal changes in the extent of soil erosion by wind and water in the Qaidam Basin from 2000 to 2018 and the impact of LUCC on them. From 2000 to 2018, with global climate change, the areas and intensities of soil erosion by wind decreased, whereas those of soil erosion by water increased. With increased human activities, approximately 12.96% of the total area underwent conversion of the type of use: the areas of cropland, woodland, grassland, and construction land increased, whereas the areas of shrubbery, desert, and other unused land decreased. Land use/cover changes are positive to the soil erosion of water but negative to the soil erosion of wind. Among them, the changes in vegetation coverage of other unused land and grassland contributed to 83.19% of the total reduction in soil erosion by water. Converting other unused land to grassland reduced the total reductions in soil erosion by wind by 94.69%. These results indicate that the increase in vegetative cover and area of grasslands in the Qaidam Basin had a positive impact on the reduction in soil erosion. It is recommended that the arrangement of grasses, shrubs, and trees be optimized to prevent compound erosion by wind and water for protecting regional ecological environments.
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    Quantifying cover crop effects on soil health and productivity
    Jian, Jinshi; Du, Xuan; Stewart, Ryan D. (2020-04)
    The dataset presented here supports the research paper entitled "A calculator to quantify cover crop effects on soil health and productivity". Soil health (sometimes used synonymously with soil quality) is a concept that describes soil as a living system to sustain plants, animals, and human. Soil physical, chemical, and biological properties, along with their interactions, are required to quantify soil health. The use of cover crops in agricultural rotations may enhance soil health, yet there has been little progress in understanding how external factors such as climate, soil type, and agronomic practices affect soil and cash crop responses. In response, this dataset compiles measurements from 281 studies and provides an analysis of field-measured changes in 38 soil health indicators due to cover crop usage. Environmental and background indicators were also compiled to assess how climatic and management practices affect soil and cash crop responses to cover crops, with specific categories including climate type (tropical, arid, temperate, and continental), soil texture (coarse, medium, and fine), cover crop type (legume, grass, multi-species mixture, and other), and cash crop type (corn, soybean, wheat, vegetable, corn-soybean rotation, corn-soybean-wheat rotation, and other). An unbalanced analysis of variation was used to determine the hierarchy of most to least important factors that affected responsiveness of each soil health indicator. Based on the hierarchy structure, a soil health calculator was then developed to quantify the response of 13 parameters - erosion, runoff, weed suppression, soil aggregate stability, leaching, infiltration, microbial biomass carbon, soil bulk density, soil organic carbon, soil nitrogen, microbial biomass nitrogen, cash crop yield, and saturated hydraulic conductivity - to cover crops. The presented data in the calculator report the mean change in parameter values based on all combinations of climate, soil texture, cover crop type, and cash crop type. (c) 2020 The Author(s). Published by Elsevier Inc. This is an open access article under the CC BY license. (http://creativecommons.org/licenses/by/4.0/)
  • Soil properties affect crop yield changes under conservation agriculture: A systematic analysis
    Ren, Xiaohua; Zou, Wenjing; Jiao, Juying; Stewart, Ryan D.; Jian, Jinshi (Wiley, 2023-09-13)
    Conservation agriculture (CA) has the potential to sustain soil productivity and benefit agroecosystems, yet it is not fully understood how yield responses of different cropping systems are affected by inherent soil characteristics, for example, texture and dynamic soil properties, such as aggregation, nutrients and erosion. In this study, we conducted a systematic review to compare crop yield from cropland with conventional management versus different CA practices, specifically reduced- or no-tillage, agroforestry, organic farming and cover crops. The data were first analysed for different climatic regions, soil textures and cash crop types. We then quantified how yield responses correlated with soil properties change under different CA practices. The results showed that CA practices were associated with an overall mean crop yield increase of 12%. This response was primarily driven by corn, which had a mean yield increase of almost 41% after CA implementation, whereas other cash crops did not have significant yield responses or showed slight decreases, as rotation with mixtures of multiple cash crops had a mean decrease of 6% when using CA. The increase in corn yield after CA may be related to the enhanced ability of that crop to absorb nutrient elements (e.g. nitrogen) and reduce nutrient leaching. Agroforestry increased crop yield by 66% and cover cropping increased yield by 11%, likely due to increases in soil water content and nutrient availability and decreases in erosion and surface runoff. However, other agricultural systems showed no significant increase after CA compared with conventional row cropping practices. Using CA practices had the greatest yield benefit in tropical climates and when farming in coarse-textured soils. In addition, legumes and grass-legume mixtures resulted in significant cash crop yield increases, possibly because legumes promoted the increase of soil nitrogen and depleted soil moisture less compared with other cover crops. The results provide new insight into how interactions between soil properties and CA practices affect crop yield and at the same time can help guide the development of practical, evidence-based guidelines for using conservation practices to improve yield in corn and other cash crops.
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    Spatiotemporal Variation of Precipitation Regime in China from 1961 to 2014 from the Standardized Precipitation Index
    Yuan, Xuefeng; Jian, Jinshi; Jiang, Gang (MDPI, 2016-10-27)
    Prediction of drought and flood events can be difficult, but the standardized precipitation index (SPI) calculated from monthly data may be a useful tool for predicting future dryness/wetness events in China. The rainy season SPI was calculated from monthly precipitation data from 3804 meteorological stations in China. The spatiotemporal variation, periodic change, and trend in rainy season SPI from 1961 to 2014 in eight regions were investigated. The results indicate that the rainy season SPI is valuable for assessing dryness/wetness spatial and temporal variations. The SPI time series in the northwest and southwest show increasing trends, while northeast China, south China, and Taiwan show more than one upward/downward trend during the study period, and the SPI time series in central, east, and north China show no change in trend. South China has an approximately 10-year periodic oscillation, while the other regions show an approximately 16-year periodic oscillation. The results of this study imply that the SPI can be used to explore historical drought/flood spatiotemporal variations, as well as to predict future wetness/dryness variations.
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    What We Talk about When We Talk about Soil Health
    Stewart, Ryan D.; Jian, Jinshi; Gyawali, Ayush Joshi; Thomason, Wade E.; Badgley, Brian D.; Reiter, Mark S.; Strickland, Michael S. (American Society of Agronomy, Crop Science Society of America, and Soil Science Society of America, 2018-11-01)
    Despite a nationwide emphasis on improving soil health in the United States, current measurement protocols have little consistency. To survey assessment practices, we conducted a meta-analysis of cover crop (n = 86) and no-tillage (n = 106) studies and compiled reported indicators, cropping systems, and soil sampling protocols from each. We then analyzed which indicators significantly responded to cover crop usage after 1 yr and 2 to 3 yr. Our results showed that out of 42 indicators, only 8 were reported in >20% of studies. Thirteen indicators showed >10% relative response after 1 to 3 yr; the remainder lacked either sufficient observations or consistent results. Looking forward, we propose that emphasis should be placed on (i) pursuing dynamic indicators (e.g., aggregate stability), (ii) standardizing sampling protocols, and (iii) developing a common framework for information sharing. These efforts will generate new insight into soil health across systems, ultimately ensuring that soil health science is useful to producers and regulators.