Ecological Processes最新文献

{"title":"Decoupling effect and driving factors of carbon footprint in megacity Wuhan, Central China.","authors":"Gao Pan,&nbsp;Xinhang Li,&nbsp;Deng Pan,&nbsp;Wensheng Liu","doi":"10.1186/s13717-023-00435-y","DOIUrl":"10.1186/s13717-023-00435-y","url":null,"abstract":"<p><strong>Background: </strong>China's 35 largest cities, including Wuhan, are inhabited by approximately 18% of the Chinese population, and account for 40% energy consumption and greenhouse gas emissions. Wuhan is the only sub-provincial city in Central China and, as the eighth largest economy nationwide, has experienced a notable increase in energy consumption. However, major knowledge gaps exist in understanding the nexus of economic development and carbon footprint and their drivers in Wuhan.</p><p><strong>Methods: </strong>We studied Wuhan for the evolutionary characteristics of its carbon footprint (CF), the decoupling relationship between economic development and CF, and the essential drivers of CF. Based on the CF model, we quantified the dynamic trends of CF, carbon carrying capacity, carbon deficit, and carbon deficit pressure index from 2001 to 2020. We also adopted a decoupling model to clarify the coupled dynamics among total CF, its accounts, and economic development. We used the partial least squares method to analyze the influencing factors of Wuhan's CF and determine the main drivers.</p><p><strong>Results: </strong>The CF of Wuhan increased from 36.01 million t CO₂eq in 2001 to 70.07 million t CO₂eq in 2020, a growth rate of 94.61%, which was much faster than that of the carbon carrying capacity. The energy consumption account (84.15%) far exceeded other accounts, and was mostly contributed by raw coal, coke, and crude oil. The carbon deficit pressure index fluctuated in the range of 8.44-6.74%, indicating that Wuhan was in the relief zone and the mild enhancement zone during 2001-2020. Around the same time, Wuhan was in a transition stage between weak and strong CF decoupling and economic growth. The main driving factor of CF growth was the urban per capita residential building area, while energy consumption per unit of GDP was responsible for the CF decline.</p><p><strong>Conclusions: </strong>Our research highlights the interaction of urban ecological and economic systems, and that Wuhan's CF changes were mainly affected by four factors: city size, economic development, social consumption, and technological progress. The findings are of realistic significance in promoting low-carbon urban development and improving the city's sustainability, and the related policies can offer an excellent benchmark for other cities with similar challenges.</p><p><strong>Supplementary information: </strong>The online version contains supplementary material available at 10.1186/s13717-023-00435-y.</p>","PeriodicalId":11419,"journal":{"name":"Ecological Processes","volume":"12 1","pages":"23"},"PeriodicalIF":4.8,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10189220/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"9516624","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Current and near-term advances in Earth observation for ecological applications.","authors":"Susan L Ustin,&nbsp;Elizabeth M Middleton","doi":"10.1186/s13717-020-00255-4","DOIUrl":"https://doi.org/10.1186/s13717-020-00255-4","url":null,"abstract":"<p><p>There is an unprecedented array of new satellite technologies with capabilities for advancing our understanding of ecological processes and the changing composition of the Earth's biosphere at scales from local plots to the whole planet. We identified 48 instruments and 13 platforms with multiple instruments that are of broad interest to the environmental sciences that either collected data in the 2000s, were recently launched, or are planned for launch in this decade. We have restricted our review to instruments that primarily observe terrestrial landscapes or coastal margins and are available under free and open data policies. We focused on imagers that passively measure wavelengths in the reflected solar and emitted thermal spectrum. The suite of instruments we describe measure land surface characteristics, including land cover, but provide a more detailed monitoring of ecosystems, plant communities, and even some species then possible from historic sensors. The newer instruments have potential to greatly improve our understanding of ecosystem functional relationships among plant traits like leaf mass area (LMA), total nitrogen content, and leaf area index (LAI). They provide new information on physiological processes related to photosynthesis, transpiration and respiration, and stress detection, including capabilities to measure key plant and soil biophysical properties. These include canopy and soil temperature and emissivity, chlorophyll fluorescence, and biogeochemical contents like photosynthetic pigments (e.g., chlorophylls, carotenoids, and phycobiliproteins from cyanobacteria), water, cellulose, lignin, and nitrogen in foliar proteins. These data will enable us to quantify and characterize various soil properties such as iron content, several types of soil clays, organic matter, and other components. Most of these satellites are in low Earth orbit (LEO), but we include a few in geostationary orbit (GEO) because of their potential to measure plant physiological traits over diurnal periods, improving estimates of water and carbon budgets. We also include a few spaceborne active LiDAR and radar imagers designed for quantifying surface topography, changes in surface structure, and 3-dimensional canopy properties such as height, area, vertical profiles, and gap structure. We provide a description of each instrument and tables to summarize their characteristics. Lastly, we suggest instrument synergies that are likely to yield improved results when data are combined.</p>","PeriodicalId":11419,"journal":{"name":"Ecological Processes","volume":"10 1","pages":"1"},"PeriodicalIF":4.8,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1186/s13717-020-00255-4","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"10739727","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}