Showing papers in "Ecological Indicators in 2022"

TL;DR: Wang et al. as discussed by the authors proposed a framework that integrates the system dynamics (SD) model, patch-generating land use simulation (PLUS) model and integrated valuation of Ecosystem Service and Tradeoffs (InVEST) model to dynamically simulate changes in land use/cover change (LUCC) and carbon storage (CS) at the city level based on SSP-RCP scenarios provided by the CMIP6.

TL;DR: Zhang et al. as mentioned in this paper analyzed a long-term (nine years) high-throughput sequencing dataset by network analysis to illustrate how the microbial stability varies among seasons in lake ecosystems.

TL;DR: In this article , the spatial and temporal distribution characteristics of carbon emissions in the Yellow River Delta from 2000 to 2019 by constructing a carbon emission model, carbon footprint and Moran's I index were explored.

TL;DR: In this paper , the long-term (1982-2020) satellite-derived Normalized Difference Vegetation Index (NDVI) data sets and climatic factors were employed to analyze the spatiotemporal patterns of the vegetation dynamics in Mu Us Sandy Land (MUSL).

TL;DR: Wang et al. as mentioned in this paper employed patch-generating land use simulation (PLUS) model coupled with multiple linear regression and a Markov chain model to project the landscape patterns in 2050.

TL;DR: In this article , the authors explored the spatiotemporal variation in vegetation net primary productivity (NPP), analyzed the relationships between NPP and its influencing factors, and evaluated the vegetation carbon sink capacity.

TL;DR: Zhang et al. as discussed by the authors proposed a technical framework for the delineation of ecological security patterns at the urban agglomeration scale with the objective of protecting and restoring mountains-rivers-forests-farmlands-lakes-grasslands.

TL;DR: In this paper , a new strategy to optimize ecological sources and resistance surfaces was proposed, and the optimal diffusion distance of each existing ecological source with poor landscape connectivity was analyzed to meet future needs.

TL;DR: Wang et al. as discussed by the authors explored the spatial and temporal variation of wetland types using dynamic analysis and correlation indices of land change, and quantified the degree of impact of changes on ecosystem service value based on the equivalence factor method.

TL;DR: Based on the exposure-sensitivity-adaptability (ESSA) framework and earth observation data, the authors proposes an ecological vulnerability evaluation index system that reflects the impacts of natural and human stressors and assesses the ecological vulnerability in the Yellow River Basin during different policy periods.

TL;DR: Wang et al. as mentioned in this paper used the large landscape connectivity index and the probability of connectivity values to determine the ecological source areas, taking landscape connectivity into account, and selected 20 ecological source sites based on dIIC and dPC values and area size.

TL;DR: In this article , the authors proposed an ESP-FLUS model to predict the future land use pattern with a comprehensive consideration of ecological protection, where the ecological security pattern (ESP) was integrated from four ecological aspects (i.e., hydrology, geology, biodiversity, and recreation).

TL;DR: Wang et al. as mentioned in this paper proposed a multi-scale land use optimization method based on benefit coupling evaluation, BP-ANN and CLUE-S models, which can better meet the land space demand for food security and ecological protection in the future.

TL;DR: In this paper , the optimal spatial scale needed to analyze spatiotemporal changes in landscape ecological risk on Haitan Island from 2000 to 2020 was investigated, and the optimal grid size and scale based on semivariogram analysis were 75 m and 500 × 500 m, respectively.

TL;DR: Wang et al. as discussed by the authors used bibliometric analysis to comprehensively review the progress of global research in ecological security from 2000 to 2020 to provide an overview for future directions.

TL;DR: In this paper , the authors evaluated the coupling coordination degree between the ecological environment and economy of counties in northern China by combining an entropy method and a coupling coordination model, which revealed the spatial agglomeration characteristics and factors that influence the coordination degree of the ecological-economic system in the region.

TL;DR: Zhang et al. as discussed by the authors employed the coupling coordination degree (CCD) model to explore the change characteristics between the two integrated systems and subsystems of urbanization and ecosystem service value (ESV).

TL;DR: In this paper , the relationship among GDP, CO2 emissions, and renewable energy use has been investigated, starting from a systematic review that has noticed the presence of three clusters focused on: CO 2 emissions, GDP, and energy consumption.

TL;DR: In this article , a framework for the assessment of regional spatial patterns in land use/cover changes (LUCC) and ecosystem service value (ESV) was established; the framework relies on the application of a classical spatial autocorrelation model.

TL;DR: In this article , a review aimed to provide comprehensive knowledge about the behaviour and the effects of MP/NPs particles on animals, humans, and the environment through the "One Health" concept, which provides an innovative and suitable perspective focused on the intersection of the above-mentioned three areas.

TL;DR: In this article , the food production model, InVEST model, and RUSLE model were used to quantitatively assess three ecosystem services (food production, water yield, and soil conservation) in the Yellow River Basin (YRB) from 2000 to 2018.

TL;DR: In this paper , the authors evaluated the coupling coordination degree (CCD) between socioeconomic development and ecological environment in prefecture-level cities on the Loess Plateau and found that more than 70% of the cities showed primary coordination and tiny coordination and no city located to good coordination.

TL;DR: Wang et al. as mentioned in this paper used statistical methods such as Dimidiate pixel model, linear regression, Moran index, and coefficient of variation to conduct a spatio-temporal analysis of the vegetation coverage in the Yellow River Basin.

TL;DR: In this paper , the authors developed and applied an ecological risk assessment framework that integrates landscape pattern characteristics and landscape vulnerability dynamics to analyze spatiotemporal variations in landscape ecological risk in the Yangtze River Economic Belt from 2000 to 2018.

TL;DR: Zhang et al. as discussed by the authors analyzed the importance and connectivity of ecological corridors using a gravity model and the probability of connectivity index and identified key restoration and protection areas in Jingmen.

TL;DR: In this article , a comprehensive evaluation system was built to quantify the new-type urbanization level of urban agglomeration in the middle reaches of the Yangtze River from 2006 to 2017.

TL;DR: In this paper , the authors selected the Google Earth Engine platform to select 100m resolution PROBA-V remote sensing images from 2018 of Zambia, in central Africa, in order to conduct grassland resource surveys for the scientific management of grassland resources.

TL;DR: Wang et al. as discussed by the authors used the index system construction method to evaluate the comprehensive level of urbanization and ecological environment, and used the coupling coordination degree model (CCDM), relative development degree model, and geographically and temporally weighted regression (GTWR) to explore the dynamic changes and spatiotemporal heterogeneity of the coupling relationship between urbanisation and the ecological environment.

TL;DR: In this paper , a patch-generating land use simulation (PLUS) was used to simulate the ESV spatial distribution considering the influences of temperature (TEM), precipitation (PRE), NDVI, DEM, Soil organic matter content (SOMC) and Human Activity Intensity of Land Surface (HAILS) of the Aksu River Basin (ARB) in 2030.