Analyzing Land-Use Change Scenarios for Ecosystem Services and their Trade-Offs in the Ecological Conservation Area in Beijing, China

Li, Zuzheng; Cheng, Xiaoqin; Han, Hairong

doi:10.3390/ijerph17228632

Cited by 28 publications

(16 citation statements)

References 59 publications

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“…The accuracy of the model in simulating the land‐use situation of the XMA was verified by the Figure of Merit (FoM)() index. The FoM index of the FLUS model for simulating the land‐use pattern was 0.67, which proved that the FLUS model was more applicable and could simulate the future land use of the XMA better (Chen et al, 2017; Li et al, 2020). The spatial supply maps of CR, CS, and R were produced by the IUEMS model (see details in Equations () to () in Section 2.5).…”

Section: Methodsmentioning

confidence: 96%

“…ESs are not completely independent but interact with each other in a complex nonlinear relationship, of which the more typical ones are the trade‐off and synergy relationships (Li et al, 2020). The Pearson correlation coefficient r is used to characterize the trade‐off and synergy relationship between ESs in this paper, and the formula is as follows:

r = \frac{\sum_{i = 1}^{n} (x_{i} - \overset{true¯}{x}) (y_{i} - \overset{true¯}{y})}{\sqrt{\sum_{i = 1}^{n} {((), x_{i} goodbreak- \overset{x}{true})}^{2}} \sqrt{\sum_{i = 1}^{n} {((), y_{i} goodbreak- \overset{y}{true})}^{2}}}

where

r

is the correlation coefficient;

i

is the order of years, from 1 to

n

;

n

is the total number of years;

x_{i}

is one ES at a time

i

; and

y_{i}

is another ES at time

i

.…”

Section: Methodsmentioning

confidence: 99%

“…ESs are not completely independent but interact with each other in a complex nonlinear relationship, of which the more typical ones are the trade-off and synergy relationships (Li et al, 2020). The Pearson correlation coefficient r is used to characterize the trade-off and synergy relationship between ESs in this paper, and the formula is as follows:…”

Section: Analysis Of Trade-offs and Synergies Of Esmentioning

confidence: 99%

See 2 more Smart Citations

A spatially explicit framework for assessing ecosystem service supply risk under multiple land‐use scenarios in the Xi'an Metropolitan Area of China

Peng,

Zhang,

et al. 2024

Land Degrad Dev

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Rapid global urbanization has perturbed ecosystem structures and functions, resulting in ecological risk and threatening sustainable human well‐being and socioeconomic development. However, scientific indicators to analyze ecosystem service (ES) risk patterns need to be explored in detail. In addition, studies on ES supply risk are stagnating on historical or status explorations, especially from the view of disturbance from land‐use changes. This study seeks to develop a framework for modeling past‐future ES supply risk pattern evaluation and probing into ES risk patterns under different future land‐use scenarios. To achieve this objective, the framework integrates the Future Land Use Simulation (FLUS) model, the Intelligent Urban Ecosystem Management System (IUEMS) model, and an established indicator system incorporating ES supply trend, hotspots and coldspots, and ES trade‐offs, and synergies. The results show that: (1) In 2050, the supply of climate regulation in the Xi'an Metropolitan Area (XMA) will increase, while that of carbon sequestration and recreation will decrease. In 2050, the supply of climate regulation is the highest under ecological protection (EP) scenario, while the supply of carbon sequestration and recreation are the highest under cropland protection (CP) scenario. (2) From 2000 to 2050, the hotspots and coldspots of climate regulation increase in both natural development (ND) scenario and CP scenario. Notably, CP scenario experiences the most significant reduction in extremely significant hotspots and coldspots of carbon sequestration. From 2000 to 2050, at the regional and pixel scales, climate regulation and carbon sequestration mainly show trade‐offs, and carbon sequestration and recreation show synergies. (3) ES supply risk in XMA is high in the center and low in the north and south. The ES supply risk from 2000 to 2050 is increasing, with expanding “extremely high risk”, “high risk”, and “extremely safe” areas. ES supply risk management should adhere to more strict land‐use policies and guidelines, management zoning for areas with different levels of ES risk, and an accurate understanding of ES trade‐offs and synergies for scientific risk management. This study could provide theoretical and technical references for ES risk assessment research and promote scientific ecological risk management.

show abstract

Section: Methodsmentioning

confidence: 96%

r = \frac{\sum_{i = 1}^{n} (x_{i} - \overset{true¯}{x}) (y_{i} - \overset{true¯}{y})}{\sqrt{\sum_{i = 1}^{n} {((), x_{i} goodbreak- \overset{x}{true})}^{2}} \sqrt{\sum_{i = 1}^{n} {((), y_{i} goodbreak- \overset{y}{true})}^{2}}}

where

r

is the correlation coefficient;

i

is the order of years, from 1 to

n

;

n

is the total number of years;

x_{i}

is one ES at a time

i

; and

y_{i}

is another ES at time

i

.…”

Section: Methodsmentioning

confidence: 99%

Section: Analysis Of Trade-offs and Synergies Of Esmentioning

confidence: 99%

See 1 more Smart Citation

A spatially explicit framework for assessing ecosystem service supply risk under multiple land‐use scenarios in the Xi'an Metropolitan Area of China

Peng,

Zhang,

et al. 2024

Land Degrad Dev

View full text Add to dashboard Cite

show abstract

“…Therefore, the area of positive synergy between the former three pairs was increasing. Some studies concluded for other regions that grain supply and HQ are trade-offs (Li Z et al, 2020;Zhang et al, 2020). In this study, FS includes both grain and meat production.…”

Section: How Did the Ess Affect Each Other?mentioning

confidence: 96%

“…In this study, FS includes both grain and meat production. Grain production by cropland reduced HQ, so FS and HQ are trade-offs in cropland areas (Li Z et al, 2020). But for the meat production by grassland, its increase was mainly caused by forage production increases, resulting from the ecological construction on sandy land and desert.…”

Section: How Did the Ess Affect Each Other?mentioning

confidence: 99%

Relationships Between Key Dryland Ecosystem Services: A Case Study in Ordos, China

Zhao

Ding

et al. 2022

Front. Earth Sci.

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Dryland ecosystem services (ESs) have been severely harmed by global environmental changes and increased human activities. To improve ESs, it is necessary to understand how they interact in drylands. In this study, we selected Ordos dryland, which is situated in northern China, as the study area to assess its four key ESs—food supply (FS), carbon storage (CS), water yield (WY), and habitat quality (HQ)—and to identify the hotspots of multiple ES supply. Furthermore, we studied the constraint effects between ESs in Ordos in 2000, 2010, and 2020 and used a spatial trade-off model to map the trade-off and synergy areas of ESs from 2000 to 2010 and from 2010 to 2020. The results indicated that all four ESs in Ordos increased significantly over the study period. The hotspots for the supply of multiple ESs also increased in areal extent during this period, and the state of the regional ecological environment continued to improve. The constraint effect between ESs showed that as the CS increased, its constraint effect on WY and FS decreased and then increased, whereas its constraint effect on HQ only decreased; as the WY increased, its constraint effect on HQ decreased and then increased, and its constraint effect on FS continued to decrease; as the FS increased, its constraint effect on HQ continued to increase. From the change in the area of ESs trade-offs and synergies, there was an increase in the area of positive synergy for four pairs of ESs in Ordos, which were CS-WY, CS-HQ, WY-HQ, and FS-HQ. These findings help in establishing a scientific foundation for the management and optimization of ESs in drylands.

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Simulation of land use landscape pattern evolution from a multi-scenario simulation: a case study of Nansi Lake Basin in China

Han¹,

Jing²,

Liu³

2023

Environ Monit Assess

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Analyzing Land-Use Change Scenarios for Ecosystem Services and their Trade-Offs in the Ecological Conservation Area in Beijing, China

Cited by 28 publications

References 59 publications

A spatially explicit framework for assessing ecosystem service supply risk under multiple land‐use scenarios in the Xi'an Metropolitan Area of China

A spatially explicit framework for assessing ecosystem service supply risk under multiple land‐use scenarios in the Xi'an Metropolitan Area of China

Relationships Between Key Dryland Ecosystem Services: A Case Study in Ordos, China

Simulation of land use landscape pattern evolution from a multi-scenario simulation: a case study of Nansi Lake Basin in China

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