Land-Use/Land-Cover Changes and Their Influence on the Ecosystem in Chengdu City, China during the Period of 1992–2018

Due to urban expansion, economic development, and rapid population growth, land use/land cover (LULC) is changing in major cities around the globe. Quantitative analysis of LULC change is important for studying the corresponding impact on the ecosystem service value (ESV) that helps in decision-making and ecosystem conservation. Based on LULC data retrieved from remote-sensing interpretation, we computed the changes of ESV associated with the LULC dynamics using the benefits transfer method and geographic information system (GIS) technologies during the period of 1992–2018 following self-modified coefficients which were corrected by net primary productivity (NPP). This improved approach aimed to establish a regional value coefficients table for facilitating the reliable evaluation of ESV. The main objective of this research was to clarify the trend and spatial patterns of LULC changes and their influence on ecosystem service values and functions. Our results show a continuous reduction in total ESV from United States (US) $1476.25 million in 1992, to US$1410.17, $1335.10, and$1190.56 million in 2001, 2009, and 2018, respectively; such changes are attributed to a notable loss of farmland and forest land from 1992–2018. The elasticity of ESV in response to changes in LULC shows that 1% of land transition may have caused average changes of 0.28%, 0.34%, and 0.50% during the periods of 1992–2001, 2001–2009, and 2009–2018, respectively. This study provides important information useful for land resource management and for developing strategies to address the reduction of ESV

Habitat quality assessment and multi-scenario prediction of the Gansu-Qinghai section of the Yellow River Basin based on the FLUS-InVEST model

Research on the impact of land use change on regional habitat quality, in various future scenarios, can effectively aid planning and decision-making for sustainable development at a regional level. The study conducted its research in the Gansu-Qinghai Yellow River section and used ArcGIS and a land use transfer matrix to analyze the spatiotemporal pattern of land use and land cover changes. The study assessed the changes in habitat quality in the Gansu-Qinghai Yellow River region between 1990 and 2020, using the Integrated Valuation of Ecosystem Services and Trade-offs (InVEST) model, by evaluating the gains and losses. Simultaneously, 15 elements of the natural economy were chosen and examined for their temporal and spatial impact on habitat quality using the random forest model and spatially weighted regression model. To forecast land use changes in the Gansu-Qinghai Yellow River section for 2030, the Future Land Use Simulation Model (FLUS) model was utilized and a series of four scenarios (cultivated land protection scenario, ecological protection scenario, natural development scenario, and rapid development scenario) were employed. The research results indicate that over 70% of the Gansu-Qinghai Yellow River is occupied by grasslands, and only a small portion of the area, about 0.22%, is developed for construction purposes. The quality of the habitat in the Gansu-Qinghai Yellow River had a minor drop between 1990 and 2020, followed by an improvement. Habitat quality changes are primarily attributed to improvements, with variations across different areas, i.e., enhanced in the east and reduced in the central and western parts. The habitat quality of the Gansu-Qinghai Yellow River has improved in all four scenarios compared to 2020, as evidenced by the decrease in low-value habitats and increase in high-value areas. The ecological protection scenario has the highest average habitat quality value. These research results can be used to support policy development and ecological restoration initiatives in the Gansu-Qinghai Yellow River

Sustainability in China: Bridging Global Knowledge with Local Action

China’s road to sustainability has attracted global attention. Since the “Reform & Opening Up” policy, China’s rapid pace of both urbanization and industrialization has made its being the second largest economy but meantime a heavy environmental price has been paid over the past few decades for addressing the economic developmental target. Today, as the biggest developing country, China needs to take more responsibilities for constructing its local ecological-civilization society as well as for addressing the global challenges such as climate change, resources scary and human beings well-fare; therefore, we need to have deeper understandings into China’s way to sustainability at very different levels, both spatially and structurally, concerns ranging from generating sustainable household livelihoods to global climate change, from developing technological applications to generate institutional changes. In this spirit, this publication, “Sustainability in China: Bridging Global Knowledge with Local Action” aims to investigate the intended and spontaneous issues concerning China’s road to sustainability in a combined top-down and bottom-up manner, linking international knowledge to local-based studies

Toward an Integrated Regional Research Program on Global Change and the Nation\u27s Major Grasslands: Second Annual Report

I DIRECTOR\u27S REPORT: A GPRC Research Framework and Thrusts B FY94 GPRC Grant Competition C Synopsis of Current Projects 1 Thrust 1: Impacts of Climate Change 2 Thrust 2: Measuring and Modeling Net Carbon Exchange 3 Other Projects D Summary and Recommendations of FY94 GPRC PI\u27s Workshop 1 Biogeochemical Cycling Group 2 Climate Scenarios Group 3 Managed and Unmanaged Ecosystem Impacts Group 4 Scaling Group 5 Actions Prompted by the Workshop E Research Integration with ARM-CART: Eco-ARM F Future Directions for the GPRC Appendix I-A: Biogeochemical Cycling Group Workshop Report • Appendix I-B: Climate Change Scenarios Group Workshop Report • Appendix I-C: Managed and Unmanaged Ecosystem Impacts Group Workshop Report • Appendix 1-0: Funded Projects Table • Appendix I-E: Core Research Program Diagram • Appendix I-F: Regional Map II RESEARCH PROGRESS REPORTS (Title, Principal Investigator, Institution): A IMPACTS OF CLIMATE CHANGE 1 Process Studies Effects of Altered Soil Moisture and Temperature on Soil Communities, Primary Producers and Ecological Processes in Grassland Ecosystems · John M Blair, Kansas State University Impacts of global climate change on phytoplankton productivity in lakes along a thermal gradient · Kyle D Hoagland, University of Nebraska-Lincoln Natural Responses of Shallow Lakes and Wetlands for Detecting Climatic/Environmental Change · Donald C Rundquist, University of Nebraska-Lincoln 2 Climate Scenarios for Impact Analysis Space-time Local Hydrology Influenced by Changing Climatology: Disaggregation, Prediction and Comparison · Istvan Bogardi, University of Nebraska-Lincoln Observational and Numerical Study for Interannual and Interdecadel Variabilities of the Atmospheric Circulation · Tsing-Chang Chen, Iowa State University The Effect of Ecosystems on Cloud Microphysics and Aerosol Distribution · Qinghuan Han, South Dakota School of Mines and Technology Development of a Nested Regional Model for the Conterminous United States and Formation of High Resolution Climate Change Scenarios with an Application to Crop Climate Models · Linda Mearns, National Center for Atmospheric Research The detection of Climate Change Using Long Term Daily Climate Records Over Grassland Regions of the Northern Hemisphere · Michael A Palecki, University of Nebraska-Lincoln 3 Modeling Impacts of Climate Change Assessment of Climate Change on a Mixed Agricultural Landscape on the North American Great Plains · James R Brandle, University of Nebraska-Lincoln The Economic and Environmental Impact of Major Shifts in Land Use into Energy Biomass Production for Part of the Great Plains · Paul T Dyke, Texas A&M University Local and Regional Scaling With a Spatially Explicit Ecological Model · George P Malanson, University of Iowa Potential Global Warming Impacts on Vegetation Distribution, Productivity, and Hydrology at Landscape to Regional Scales in the Great Plains Region · Ronald P Neilson, Oregon State University B MEASUREMENT AND MODELING OF NET CARBON EXCHANGE 1 Process Studies Carbon, Water, and Energy Fluxes From a Tallgrass Prairie: A Long-term investigation of Biological, Environmental, and Land Use Factors · Jay M Ham, Kansas State University An Integrated Investigation of Methane and Carbon Dioxide Fluxes in Mid-Latitude Prairie Wetlands: Micrometeorological Measurements, Process-Level Studies and Modeling · Shashi B Verma, University of Nebraska-Lincoln 2 Modeling Studies Regional projections of C Dynamics with Global Change in the Central US Edward T Elliott, Colorado State University Assessment of Climate and Management Induced Directional Changes in Great Plains Vegetation with NDVI and Stable Carbon Isotopes Larry L Tieszen, Augustana College C DETECTION OF CLIMATE CHANGE Climate Change in the Mid-continent of North America William D Gosnold, University of North Dakota 105 Satellite Observation of Lake Ice as a Robust Indicator of Regional Climate Change Thomas M Ullesand, University of Wisconsin-Madison Appendix II-A: Author Index Great Plains Regional Center for Global Environmental Change 20 LW Chase Hall University of Nebraska-Lincoln PO Box 830725 Lincoln, NE 68583-0725 Phone 4021472-7887 Fax 4021472-6614 E-mail agme022@unlvmunledu ACKNOWLEDGEMENT This material is based upon work supported by the US Department of Energy under Cooperative Agreement No DE-FC03-90ER61 01 O Any opinions, findings, and conclusions or recommendations expressed in this publication are those of the authors and do not necessarily reflect the views of the US Department of Energ

Machine Intelligence in Africa: a survey

In the last 5 years, the availability of large audio datasets in African countries has opened unlimited opportunities to build machine intelligence (MI) technologies that are closer to the people and speak, learn, understand, and do businesses in local languages, including for those who cannot read and write. Unfortunately, these audio datasets are not fully exploited by current MI tools, leaving several Africans out of MI business opportunities. Additionally, many state-of-the-art MI models are not culture-aware, and the ethics of their adoption indexes are questionable. The lack thereof is a major drawback in many applications in Africa. This paper summarizes recent developments in machine intelligence in Africa from a multi-layer multiscale and culture-aware ethics perspective, showcasing MI use cases in 54 African countries through 400 articles on MI research, industry, government actions, as well as uses in art, music, the informal economy, and small businesses in Africa. The survey also opens discussions on the reliability of MI rankings and indexes in the African continent as well as algorithmic definitions of unclear terms used in MI.Comment: Accepted and to be presented at DSAI 202

LIPIcs, Volume 277, GIScience 2023, Complete Volume

LIPIcs, Volume 277, GIScience 2023, Complete Volum

Combating Misinformation in the Age of LLMs: Opportunities and Challenges

Misinformation such as fake news and rumors is a serious threat on information ecosystems and public trust. The emergence of Large Language Models (LLMs) has great potential to reshape the landscape of combating misinformation. Generally, LLMs can be a double-edged sword in the fight. On the one hand, LLMs bring promising opportunities for combating misinformation due to their profound world knowledge and strong reasoning abilities. Thus, one emergent question is: how to utilize LLMs to combat misinformation? On the other hand, the critical challenge is that LLMs can be easily leveraged to generate deceptive misinformation at scale. Then, another important question is: how to combat LLM-generated misinformation? In this paper, we first systematically review the history of combating misinformation before the advent of LLMs. Then we illustrate the current efforts and present an outlook for these two fundamental questions respectively. The goal of this survey paper is to facilitate the progress of utilizing LLMs for fighting misinformation and call for interdisciplinary efforts from different stakeholders for combating LLM-generated misinformation.Comment: 9 pages for the main paper, 35 pages including 656 references, more resources on "LLMs Meet Misinformation" are on the website: https://llm-misinformation.github.io

Tracing back the source of contamination

From the time a contaminant is detected in an observation well, the question of where and when the contaminant was introduced in the aquifer needs an answer. Many techniques have been proposed to answer this question, but virtually all of them assume that the aquifer and its dynamics are perfectly known. This work discusses a new approach for the simultaneous identification of the contaminant source location and the spatial variability of hydraulic conductivity in an aquifer which has been validated on synthetic and laboratory experiments and which is in the process of being validated on a real aquifer