Impacts of Changes in Oasis Farmland Patterns on Carbon Storage in Arid Zones—A Case Study of the Xinjiang Region DOI Creative Commons
Shanshan Meng, Jianli Ding,

Jinjie Wang

et al.

Land, Journal Year: 2024, Volume and Issue: 13(12), P. 2026 - 2026

Published: Nov. 27, 2024

Xinjiang is a representative dry area in China characterized by oasis agriculture. In recent decades, the amount of farmland has increased considerably. For regional objectives “carbon peaking and carbon neutrality”, it essential to investigate effects induced large-scale changes farmland. This research integrates PLUS InVEST models calculate resulting from spatiotemporal distribution Xinjiang. It quantitatively assesses land-use patterns storage under four scenarios for 2035—natural development (ND), economic (ED), ecological protection (EP), (FP)—and explores spatial agglomeration degree effect cultivated land change. The analysis reveals following: (1) From 1990 2020, showed trend first decreasing then increasing, total increase 33,328.53 km2 over 30-year period. newly added primarily came grassland unused land. (2) terrestrial ecosystem with an 57.49 Tg 30 years. centroid was located northwestern part Bayingolin Mongol Autonomous Prefecture, showing overall southwestward shift. Changes contributed 45.03 Tg. contribution 3.42%. (3) 2035, value different will compared sink be maximum scenario. (4) There strong positive correlation between caused change Xinjiang, there are more hot spots than cold spots. transformation have characteristics “high-high” clustering “low-low” clustering. Future territorial planning should comprehensively coordinate conservation measures, improve capacity, achieve green sustainable development.

Language: Английский

Study on the driving mechanism of spatio-temporal non-stationarity of vegetation dynamics in the Taihangshan-Yanshan Region DOI Creative Commons

Jiao Pang,

Meiqing Wang, Huicong Zhang

et al.

Ecological Indicators, Journal Year: 2025, Volume and Issue: 170, P. 113084 - 113084

Published: Jan. 1, 2025

Language: Английский

Citations

1
Temporal and Spatial Carbon Stock Changes and Driving Mechanisms Based on Land Use Multi‐Scenario Modeling: An Assessment of SDGs15.3—A Case Study of the Central Yunnan Urban Agglomeration, China DOI Open Access
G. Chen, Longjiang Zhang, Dandan Zhang

et al.

Land Degradation and Development, Journal Year: 2025, Volume and Issue: unknown

Published: March 4, 2025

ABSTRACT Carbon stock is a key element of land‐based ecosystems and serves as one the indicators for assessing SDG 15.3, which undergoes direct or indirect effects due to changes in land use. Utilizing central Yunnan urban agglomeration (CYUA) study region, we constructed Markov‐Multi‐Objective‐patch‐generating use simulation (Markov‐MOP‐PLUS) coupled model across four distinct scenarios: sustainable development scenario (SDS), economic (EDS), ecological protection (EPS), natural (NDS) year 2030. The Integrated Valuation Ecosystem Services Trade‐offs (InVEST) was employed carbon spatially identifying comparatively analyzing over time different areas reserves region between 2000 We used optimal parameter geographic detector (OPGD) exploring driving factors spatial differentiation stocks quantitatively 15.3. revealed that according scenarios modeled, region's future expected show expanded watershed construction zones. Water most rapidly EPS, with NDS SDS behind; highest growth rate built‐up EDS, followed by NDS. estimated 2030, under scenarios, are ranked follows: EPS (2.581 × 10 9 tons) > (2.571 (2.570 EDS (2.567 tons), suggesting measures can promote recovery regional ecosystems' stocks. spatiotemporal variation influenced multiple factors, slope being dominant factor region. Furthermore, interactions among these not independent their impact on 15.3.1 indices 2030 all decreasing trend, although situation degradation has improved, none have met 15.3 target. This research offers valuable guidance policymakers working targets planning.

Language: Английский

Citations

0
Spatial–Temporal Pattern Analysis and Development Forecasting of Carbon Stock Based on Land Use Change Simulation: A Case Study of the Xiamen–Zhangzhou–Quanzhou Urban Agglomeration, China DOI Creative Commons
Suiping Zeng, Xinyao Liu, Jian Tian

et al.

Land, Journal Year: 2024, Volume and Issue: 13(4), P. 476 - 476

Published: April 7, 2024

The spatial–temporal distribution and evolution characteristics of carbon stock under the influence land use changes are crucial to scientific management environmental resources optimization spatial layout. Taking Xiamen–Zhangzhou–Quanzhou urban agglomeration in southeastern coastal region China as an example, based on seven types from 1990 2020, including cultivated land, woodland, construction we quantitatively investigate patterns development correlation distribution. Additionally, two scenarios for ecological priorities 2060 established effects stock. results indicate that (1) research area has formed a pattern centered around eastern bay area, with western forest belt serving barriers. Carbon is influenced by type, total exhibits aggregation phenomenon characterized “low southeast, high north, medium center”. (2) Distance trunk secondary roads, elevation, slope, watershed borders, population size, gross domestic product (GDP) factors main drivers growth types. primary causes reduction widespread conversion grassland into well water unused land. (3) In 2060, there will be decrease 41,712,443.35 Mg priority scenario compared 29,577,580.48 scenario. estimated varies 12,134,862.88 Mg. average storage Zhangpu County, Quangang Jimei County expected rise one level protection scenario, indicating vast can become potential maintain It encourage coordinated peri-urban agroforestry barriers, establish harmonious at scale agglomerations.

Language: Английский

Citations

3
Analysis of Spatiotemporal Change and Driving Factors of NPP in Qilian Mountains From 2000 to 2020 DOI
Chuan Wang, Chuan Wang, Wenzhi Zhao

et al.

Rangeland Ecology & Management, Journal Year: 2024, Volume and Issue: 96, P. 56 - 66

Published: June 13, 2024

Language: Английский

Citations

1
Mechanisms for carbon stock driving and scenario modeling in typical mountainous watersheds of northeastern China DOI
Jin Zhang,

Wenguang Zhang,

Xin-Yan Zhang

et al.

Environmental Monitoring and Assessment, Journal Year: 2024, Volume and Issue: 196(9)

Published: Aug. 8, 2024

Language: Английский

Citations

1
Impacts of Changes in Oasis Farmland Patterns on Carbon Storage in Arid Zones—A Case Study of the Xinjiang Region DOI Creative Commons
Shanshan Meng, Jianli Ding,

Jinjie Wang

et al.

Land, Journal Year: 2024, Volume and Issue: 13(12), P. 2026 - 2026

Published: Nov. 27, 2024

Xinjiang is a representative dry area in China characterized by oasis agriculture. In recent decades, the amount of farmland has increased considerably. For regional objectives “carbon peaking and carbon neutrality”, it essential to investigate effects induced large-scale changes farmland. This research integrates PLUS InVEST models calculate resulting from spatiotemporal distribution Xinjiang. It quantitatively assesses land-use patterns storage under four scenarios for 2035—natural development (ND), economic (ED), ecological protection (EP), (FP)—and explores spatial agglomeration degree effect cultivated land change. The analysis reveals following: (1) From 1990 2020, showed trend first decreasing then increasing, total increase 33,328.53 km2 over 30-year period. newly added primarily came grassland unused land. (2) terrestrial ecosystem with an 57.49 Tg 30 years. centroid was located northwestern part Bayingolin Mongol Autonomous Prefecture, showing overall southwestward shift. Changes contributed 45.03 Tg. contribution 3.42%. (3) 2035, value different will compared sink be maximum scenario. (4) There strong positive correlation between caused change Xinjiang, there are more hot spots than cold spots. transformation have characteristics “high-high” clustering “low-low” clustering. Future territorial planning should comprehensively coordinate conservation measures, improve capacity, achieve green sustainable development.

Language: Английский

Citations

0