Millions of metric tons of plastics are produced annually and transported from land to the oceans. Finding the fate of the plastic debris will help define the impacts of plastic pollution in the ocean. Here, we report the abundances of microplastic in the deepest part of the world's ocean. We found that microplastic abundances in hadal bottom waters range from 2.06 to 13.51 pieces per litre, several times higher than those in open ocean subsurface water. Moreover, microplastic abundances in hadal sediments of the Mariana Trench vary from 200 to 2200 pieces per litre, distinctly higher than those in most deep sea sediments. These results suggest that manmade plastics have contaminated the most remote and deepest places on the planet. The hadal zone is likely one of the largest sinks for microplastic debris on Earth, with unknown but potentially damaging impacts on this fragile ecosystem.
Land surface processes and their coupling to the atmosphere over the Tibetan Plateau (TP) play an important role in modulating the regional and global climate. Therefore, identifying and quantifying uncertainty in these land surface model (LSM) processes are essential for improving climate models. The specifications of land cover and soil texture types, intertwined with the uncertainties in associated vegetation and soil parameters in LSMs, are significant sources of uncertainty due to the lack of detailed land survey in the TP. To differentiate the effects of land cover or soil texture specifications in the Noah with Multiple Parameterizations (Noah-MP) LSM from the effects of uncertainties in the model parameters, this study first identified the most sensitive vegetation and soil parameters through global sensitivity analysis and then conducted parametric ensemble simulations using two land cover data sets and two soil texture data sets over the central TP to estimate their corresponding impacts on the overall model responses. The distinction level and the Kolmogorov-Smirnov test were then applied to assess the differences between the results from parametric ensemble simulations using different land cover or soil texture data sets. The results show that the simulated energy and water fluxes over the central TP are dominated by soil parameters. The canopy height is the most sensitive vegetation parameter, and the Clapp-Hornberger b parameter (the exponent in the function that relates soil water potential and water content) is the most sensitive soil parameter. Relative to the background parametric uncertainties, the Noah-MP LSM could not sufficiently distinguish the effects of changes between forested types or soil texture types, which highlight the need for further quantifying and reducing the parametric uncertainties in LSMs. Further analysis shows significant sensitivities of the distinction level and changes in model response to annual precipitation and vegetation fraction. This work provides a scientific reference for assessing the impacts of land cover or soil texture changes on Noah-MP simulations under future climate change conditions.
Straw incorporation (SI) is considered a valid agricultural measure for ameliorating soil quality and sequestrating soil C. This study aimed to quantitatively summarize the response of cereal yield to SI management. Our results showed that compared with straw removal, SI could significantly enhance cereal yield by 7% over all of China across the 9‐yr period. In all regions, SI in coarse‐textured soils increased yields more than in fine‐textured soils. Straw incorporation resulted in greater yield increases for upland crops compared with rice (Oryza sativa L.) cropping, and for rotary tillage compared with plowing and no tillage. Overall, SI‐induced cereal yield increases were greater in areas with a lack of soil nutrients and soil water. The SI‐induced increases of 1 t ha−1 of soil organic C (SOC) storage could increase cereal yield by 44 kg ha−1. If half or full amounts of cereal straw is returned across all of China's agricultural regions, cereal yields would increase by an average of 2.84 and 5.07 Tg yr−1, respectively, which would contribute to achieving the increasing yield requirements of China.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
customersupport@researchsolutions.com
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.