Assessment and Enhancement of Ecosystem Service Supply Efficiency Based on Production Possibility Frontier: A Case Study of the Loess Plateau in Northern Shaanxi DOI Open Access

Zhenjun Yan,

Yirong Wang,

Hu Xu

et al.

Sustainability, Journal Year: 2023, Volume and Issue: 15(19), P. 14314 - 14314

Published: Sept. 28, 2023

Enhancing the supply efficiency of ecosystem services plays a central role in improving both natural ecosystems and human well-being. Taking Loess Plateau Northern Shaanxi as an example, this study utilizes InVEST to assess water yield habitat quality. The optimal solutions for combination these two are calculated on basis Pareto principle. production possibility frontier curves fitted, services’ is measured. Furthermore, employs ordinary least squares geographically weighted regression analyze dominant factors affecting efficiency. results comprise following findings: (1) There eighteen representing combinations between services. (2) increases from northwest southeast spatial distribution. (3) vary among different zones Population, hydrology, gross domestic product (GDP) general-efficiency, sub-low-efficiency, low-efficiency zones, respectively. Hydrology, NDVI, GDP sub-high-efficiency zone, while GDP, terrain, population high-efficiency zone. In conclusion, paper proposes recommendations reducing trade-offs enhancing These include dynamic supervising moderate greening stabilizing general-efficiency development intensity low- sub-low-efficiency zones. reveals potential approaches offers guidance formulating ecological protection plans.

Language: Английский

Extreme degradation of alpine wet meadow decelerates soil heat transfer by preserving soil organic matter on the Qinghai–Tibet Plateau DOI
Zeyong Gao, Chengming Zhang,

Wengyan Liu

et al.

Journal of Hydrology, Journal Year: 2025, Volume and Issue: unknown, P. 132748 - 132748

Published: Jan. 1, 2025

Language: Английский

Citations

6
Permafrost thawing caused by the China-Russia Crude oil pipeline based on multi-type data and its impacts on geomorphological reshaping and water erosion DOI
Kai Gao, Guoyu Li,

Yapeng Cao

et al.

CATENA, Journal Year: 2024, Volume and Issue: 242, P. 108134 - 108134

Published: June 4, 2024

Language: Английский

Citations

16
Assessment and multi-scenario prediction of ecosystem services in the Yunnan-Guizhou Plateau based on machine learning and the PLUS model DOI Creative Commons
Yuan Li, Yuling Peng,

H. P. Peng

et al.

Frontiers in Ecology and Evolution, Journal Year: 2025, Volume and Issue: 13

Published: Feb. 18, 2025

Introduction Machine learning techniques, renowned for their ability to process complex datasets and uncover key ecological patterns, have become increasingly instrumental in assessing ecosystem services. Methods This study quantitatively evaluates individual services—such as water yield, carbon storage, habitat quality, soil conservation—on the Yunnan-Guizhou Plateau years 2000, 2010, 2020. A comprehensive service index is employed assess overall capacity, revealing spatiotemporal variations services exploring trade-offs synergies among them. Additionally, machine models identify drivers influencing services, informing design of future scenarios. The PLUS model used project land use changes by 2035 under three scenarios—natural development, planning-oriented, priority. Based on simulation results these scenarios, InVEST applied evaluate various Results During 2000-2020, exhibited significant fluctuations, driven synergies. Land vegetation cover were primary factors affecting with priority scenario demonstrating best performance across all Discussion research integrates model, providing more efficient data interpretation precise design, offering new insights methodologies managing optimizing Plateau. These findings contribute development effective protection sustainable strategies, applicable both plateau similar regions.

Language: Английский

Citations

1
Investigating the regional ecological environment stability and its feedback effect on interference using a novel vegetation resilience assessment model DOI

Jiping Yao,

Guoqiang Wang,

Ruihong Yu

et al.

The Science of The Total Environment, Journal Year: 2024, Volume and Issue: 930, P. 172728 - 172728

Published: April 24, 2024

Language: Английский

Citations

8
Considering Climatic Factors, Time Lag, and Cumulative Effects of Climate Change and Human Activities on Vegetation NDVI in Yinshanbeilu, China DOI Creative Commons
Sinan Wang, Xiaomin Liu, Yingjie Wu

et al.

Plants, Journal Year: 2023, Volume and Issue: 12(18), P. 3312 - 3312

Published: Sept. 19, 2023

Climate and human activities are the basic driving forces that control influence spatial distribution change of vegetation. Using trend analysis, Hurst index, correlation Moran path residual other methods, effects climate factors on vegetation were analyzed. The results show that: (1) research area's normalized difference index (NDVI) exhibited a substantial upward from 2001 to 2020, increasing at rate 0.003/a, cover was generally healthy. constant NDVI region made up 78.45% entire area, grassland, cultivated land, forest land showed most visible aggregation features. (2) Vegetation is mainly promoted by water heat, particularly precipitation, have major impact plants, with direct precipitation growth being much greater than indirect effect through temperature. (3) residuals obvious variability, presenting characteristic high in south low north. this study can provide basis for scientific layout ecological protection restoration projects Yinshanbeilu area.

Language: Английский

Citations

9
Permafrost Dynamics Observatory: 3. Remote Sensing Big Data for the Active Layer, Soil Moisture, and Greening and Browning DOI Creative Commons
Elizabeth Wig, Kevin Schaefer, Roger Michaelides

et al.

Earth and Space Science, Journal Year: 2025, Volume and Issue: 12(1)

Published: Jan. 1, 2025

Abstract Because of the remote nature permafrost, it is difficult to collect data over large geographic regions using ground surveys. Remote sensing enables us study permafrost at high resolution and areas. The Arctic‐Boreal Vulnerability Experiment's Permafrost Dynamics Observatory (PDO) contains about subsidence, active layer thickness (ALT), soil water content, table depth, derived from airborne radar measurements 66 image swaths in 2017. With nearly 58,000,000 pixels available for analysis, this set new discoveries can corroborate findings previous studies across region. We analyze distributions these variables use a space‐for‐time substitution enable interpretation effects climate trends. Higher volumetric content (VWC) associated with lower ALT suggesting that Arctic may become drier as warms. Soil VWC bimodal, saturated occurring more commonly burned areas, while unburned areas are unsaturated. All show statistically significant differences one land cover type another; particular, cropland has thicker layers developed seasonal subsidence than most other types, potentially related disturbance thaw. While vegetation browning not strongly any measured variables, greening less higher bulk VWC.

Language: Английский

Citations

0
Climate Warming Controls Vegetation Growth with Increasing Importance of Permafrost Degradation in the Northern Hemisphere During 1982–2022 DOI Creative Commons
Yadong Liu, Xiaodong Wu, Tonghua Wu

et al.

Remote Sensing, Journal Year: 2024, Volume and Issue: 17(1), P. 104 - 104

Published: Dec. 31, 2024

In permafrost regions, vegetation growth is influenced by both climate conditions and the effects of degradation. Climate factors affect multiple aspects environment, while degradation has a significant impact on soil moisture nutrient availability, which are crucial for ecosystem health growth. However, quantitative analysis remains largely unknown, hindering our ability to predict future changes in regions. Here, we used statistical methods analyze NDVI change region from 1982 2022. We employed correlation analysis, regression residual partial least squares structural equation modeling (PLS-SEM) examine impacts different environmental changes. The results show that average study area 2022 0.39, with values 80% remaining stable or exhibiting an increasing trend. had highest air temperature, averaging 0.32, active layer thickness coming second at 0.25. plays dominant role variations, relative contribution rate 89.6%. positively coefficients 0.92. Although accounted only 7% changes, its influence demonstrated trend Overall, suggest temperature primary factor influencing variations this region.

Language: Английский

Citations

1
Effects of Thermokarst Lake Drainage on Localized Vegetation Greening in the Yamal–Gydan Tundra Ecoregion DOI Creative Commons
Aobo Liu, Yating Chen, Xiao Cheng

et al.

Remote Sensing, Journal Year: 2023, Volume and Issue: 15(18), P. 4561 - 4561

Published: Sept. 16, 2023

As the climate warms, Arctic permafrost region has undergone widespread vegetation changes, exhibiting overall greening trends but with spatial heterogeneity. This study investigates an underexamined mechanism driving heterogeneous patterns, thermokarst lake drainage, which creates drained basins (DLBs) that represent localized hotspots. Focusing on Yamal–Gydan in Siberia, we detect 2712 lakes have during period of 2000–2020, using Landsat time-series imagery and automated change detection algorithm. Vegetation changes DLBs entire area were quantified through NDVI trend analysis. Additionally, a machine learning model was employed to correlate trajectories environmental drivers. We find provide ideal conditions for plant colonization, greenness levels reaching or exceeding those surrounding within about five years. The is 8.4 times regional average, thus contributing disproportionately despite their small share. Number years since annual soil temperature, latitude, air temperature trends, summer precipitation emerged as key factors influencing DLB greening. Our highlights drainage subsequent growth important fine-scale process augmenting signals. Quantifying these dynamics critical assessing impacts change.

Language: Английский

Citations

3
Time series analysis of remotely sensed snow cover data: revealing permafrost thermal state and vegetation dynamics DOI Open Access
Sebastian Roessler, A.J. Dietz, Samuel Schilling

et al.

Published: June 7, 2024

Snow cover plays a crucial role in climate change and is considered an essential variable by the Global Climate Observing System (GCOS).To accurately monitor daily snow extent, optical medium-resolution remote sensing systems like MODIS VIIRS are employed.DLR's SnowPack (GSP) product, derived from MODIS/VIIRS data, addresses data gaps caused clouds or polar night, providing gap-free datasets since February 2000.The extended time series allows identification of trends duration (SCD), which has implications for thermal state permafrost soils vegetation dynamics.Snow acts as insulating barrier against colder winter air temperatures, enabling underlying layer to retain higher temperatures.The 23-year dataset SCD GSP both determination long-term average derivation trends.We compared mean trend with annual changes parameters describing horizontal vertical well land classifications (both provided ESA CCI).Regarding "Greening Arctic" we found classes, but observed period 2000 there was little dynamism, this only slightly reflected SCD.Obvious developments were -mainly degradation, increases also noted, similar positive duration.Changes Active Layer Thickness (ALT) could be best explained changes.Overall, additional needed make quantitative predictions about development using SCD.1

Language: Английский

Citations

0
Smartphone-based hyperspectral imaging for ice sheet and proglacial applications in South-West Greenland DOI Creative Commons
Matthias Bo Stuart, Matthew A. Davies, Callum Fisk

et al.

The Science of The Total Environment, Journal Year: 2024, Volume and Issue: 951, P. 175516 - 175516

Published: Aug. 13, 2024

Hyperspectral imaging is a valuable analytical technique with significant benefits for environmental monitoring. However, the application of these technologies remains limited, largely by cost and bulk associated available instrumentation. This results in lack high-resolution data from more challenging extreme settings, limiting our knowledge understanding effects climate change regions. In this article we challenge limitations through low-cost, smartphone-based hyperspectral instrument to measurement monitoring activities at Greenland Ice Sheet. Datasets are captured across variety supraglacial proglacial locations covering visible near infrared wavelengths. Our comparable existing literature, despite being instrumentation costing over an order magnitude less than currently commercial technologies. Practicalities field deployment also explored, demonstrating approach be addition research potential improve availability datasets cryosphere, unlocking wealth collection opportunities that were hitherto infeasible.

Language: Английский

Citations

0