Simulating the Impacts of Land-Use Land-Cover Changes on Cropland Carbon Fluxes in the Midwest of the United States

Understanding the major drivers of the cropland carbon fluxes is important for carbon management and greenhouse gas mitigation in agriculture. Past studies found that agricultural land-use and land-cover (LULC) changes, such as changes in cropland production technologies, tillage practices, and planted crop species, could have large impacts on carbon fluxes. However, the impacts remain highly uncertain at regional to global scales. Satellite remote sensing is commonly used to create products with geospatial information on LULC changes. This geospatial information can be integrated into biogeochemical models to simulate the spatial and temporal patterns of carbon fluxes. We used the General Ensemble Biogeochemical Modeling System (GEMS) to study LULC change impacts on cropland carbon fluxes in the Midwest USA. First we evaluated the impacts of LULC change on cropland net primary production (NPP) estimates. We found out the high spatial variability of cropland NPP across the study region was strongly related to the changes in crop species. Ignoring information about crop species distributions could introduce large biases into NPP estimates. We then investigated whether the characteristics of LULC change could impact the uncertainties of carbon flux estimates (i.e., NPP, net ecosystem production (NEP) and soil organic carbon (SOC)) using GEMS and two other models. The uncertainties of all three flux estimates were spatial autocorrelated. Land cover characteristics, such as cropland percentage, crop richness, and land cover diversity all showed statistically significant relationships with the uncertainties of NPP and NEP, but not with the uncertainties of SOC changes. The impacts of LULC change on SOC changes were further studied with historical LULC data from 1980 to 2012 using GEMS simulations. The results showed that cropland production increase over time from technology improvements had the largest impacts on cropland SOC change, followed by expansion of conservation tillage. This study advanced the scientific knowledge of cropland carbon fluxes and the impacts of various management practices over an agricultural area. The findings could help future carbon cycle studies to generate more accurate estimates on spatial and temporal changes of carbon fluxes

Multi-model Fusion Attention Network for News Text Classification

At present, the classification prediction task based on news content or news headline has the problems of inaccurate classification and attention deviation. In this paper, a multi-model fusion attention network for news text classification (MFAN) is proposed to train news content and news titles in parallel. Firstly, the multi-head attention mechanism is used to obtain the category information of news content through a dynamic word vector, focusing on the semantic information that significantly influences the downstream classification task. Secondly, the semantic information of news headlines is obtained by using the improved version of the long-short-term memory network, and the attention is focused on the words that have a great influence on the final results, which improves the effectiveness of model classification. Finally, the classification fusion module fuses the probability scores of news text and news headlines in proportion to improve the accuracy of text classification. The experimental test on the Tenth China Software cup dataset shows that the F1 - Score index of the MFAN model reaches 97.789 %. The experimental results show that the MFAN model can effectively and accurately predict the classification of news texts

Over-the-Air Testing for Connecting Faults Diagnosis in Beamforming Antenna Arrays with Short Measurement Distance

A novel diagnosis method for detecting the connecting faults (i.e., disconnected and misconnected antenna elements) in beamforming antenna array is proposed. Compared with state-of-the-art methods, the proposed diagnosis method can be conducted when the phased array operates in its default beam-steering mode. Moreover, the proposed diagnosis method is fast since it only requires a few near-field measurement positions in a very short distance (i.e., the near-field of the array). Measurement uncertainties, e.g., the scatterings from the practical testing environment, are considered in the method. Therefore, the proposed method can robustly detect beamforming array connecting faults in practical production line testing environments. The method is first validated using an 11-element dual-polarized base station (BS) antenna array at 2.7 GHz by numerical simulations. It is further experimentally validated using an eight-element single-polarized patch antenna array at 3.6 GHz. The same antenna array also serves as the probe array with only a 10-cm distance between the antenna under test (AUT) and the probe array. The diagnosis results for different types of connecting faults with numerical simulations and measurement validations have verified the effectiveness and robustness of the proposed method in practical applications.</p

Simulating the effects of management practices on cropland soilorganic carbon changes in the Temperate Prairies Ecoregion of theUnited States from 1980 to 2012

Understanding the effects of management practices on soil organic carbon (SOC) is important for design-ing effective policies to mitigate greenhouse gas emissions in agriculture. In the Midwest United States,management practices in the croplands have been improved to increase crop production and reduce SOCloss since the 1980s. Many studies of SOC dynamics in croplands have been performed to understandthe effects of management, but the results are still not conclusive. This study quantified SOC dynam-ics in the Midwest croplands from 1980 to 2012 with the General Ensemble Biogeochemical ModellingSystem (GEMS) and available management data. Our results showed that the total SOC in the croplandsdecreased from 1190 Tg C in 1980 to 1107 TgC in 1995, and then increased to 1176 TgC in 2012. Contin-uous cropping and intensive tillage may have driven SOC loss in the early period. The increase of cropproduction and adoption of conservation tillage increased the total SOC so that the decrease in the totalSOC stock after 32 years was only 1%. The small change in average SOC did not reflect the large spatialvariations of SOC change in the region. Major SOC losses occurred in the north and south of the region,where SOC baseline values were high and cropland production was low. The SOC gains took place in thecentral part of the region where SOC baseline values were moderate and cropland production was higherthan the other areas. We simulated multiple land-use land-cover (LULC) change scenarios and analyzedthe results. The analysis showed that among all the LULC changes, agricultural technology that increasedcropland production had the greatest impact on SOC changes, followed by the tillage practices, changesin crop species, and the conversions of cropland to other land use. Information on management practiceinduced spatial variation in SOC can be useful for policy makers and farm managers to develop long-termmanagement strategies for increasing SOC sequestration in different areas

Evaluating land cover influences on model uncertainties—A case study of cropland carbon dynamics in the Mid-Continent Intensive Campaign region

tQuantifying spatial and temporal patterns of carbon sources and sinks and their uncertainties acrossagriculture-dominated areas remains challenging for understanding regional carbon cycles. Character-istics of local land cover inputs could impact the regional carbon estimates but the effect has not beenfully evaluated in the past. Within the North American Carbon Program Mid-Continent Intensive (MCI)Campaign, three models were developed to estimate carbon fluxes on croplands: an inventory-basedmodel, the Environmental Policy Integrated Climate (EPIC) model, and the General Ensemble biogeo-chemical Modeling System (GEMS) model. They all provided estimates of three major carbon fluxes oncropland: net primary production (NPP), net ecosystem production (NEP), and soil organic carbon (SOC)change. Using data mining and spatial statistics, we studied the spatial distribution of the carbon fluxesuncertainties and the relationships between the uncertainties and the land cover characteristics. Resultsindicated that uncertainties for all three carbon fluxes were not randomly distributed, but instead formedmultiple clusters within the MCI region. We investigated the impacts of three land cover characteristicson the fluxes uncertainties: cropland percentage, cropland richness and cropland diversity. The resultsindicated that cropland percentage significantly influenced the uncertainties of NPP and NEP, but noton the uncertainties of SOC change. Greater uncertainties of NPP and NEP were found in counties withsmall cropland percentage than the counties with large cropland percentage. Cropland species richnessand diversity also showed negative correlations with the model uncertainties. Our study demonstratedthat the land cover characteristics contributed to the uncertainties of regional carbon fluxes estimates.The approaches we used in this study can be applied to other ecosystem models to identify the areaswith high uncertainties and where models can be improved to reduce overall uncertainties for regionalcarbon flux estimates