Impact of Future Development Scenario Selection on Landscape Ecological Risk in the Chengdu-Chongqing Economic Zone

Abstract

The management of regional eco-environmental risks is the key to promoting regional economic sustainability from the macro level, and accurate evaluation of the evolutionary trends of regional ecological risk in the future is of high importance. In order to clearly identify the possible impact of future development scenario selection for the Chengdu-Chongqing Economic Zone (C-C E Zone) on the evolution of landscape ecological risk (LER), we introduced the Patch-generating Land Use Simulation (PLUS) model to simulate land use data for the C-C E Zone from 2030 to 2050 for two scenarios: natural development (ND) and ecological protection (EP). Based on the ecological grid and landscape ecological risk index (LERI) model, the landscape ecological risk (LER) evolutionary trends seen in the C-C E Zone from 2000 to 2050 were analyzed and identified. The results showed that: (1) The PLUS model can obtain high-precision simulation results in the C-C E Zone. In the future, the currently increasing rate of land being used for construction will be reduced, the declining rates of forest and cultivated land area will also be reduced, and the amount of land being used for various purposes will remain stable going into the future. (2) This study found that the optimal size of the ecological grid in the LERI calculation of the mountainous area was 4 × 4 km. Additionally, the mean values of the LERI in 2030, 2040, and 2050 were 0.1612, 0.1628, and 0.1636 for ND and 0.1612, 0.1618, and 0.1620 for EP. (3) The hot spot analysis results showed that an area of about 49,700 km2 in the C-C E Zone from 2000 to 2050 belongs to high agglomeration of LER. (4) Since 2010, the proportions of high and extremely high risk levels have continued to increase, but under the EP scenario, the high and extremely high risk levels in 2040 and 2050 decreased from 14.36% and 6.66% to 14.33% and 6.43%. Regional analysis showed that the high and extremely high risk levels in most regions increased over 2010–2050. (5) Under the ND scenario, the proportions of grids with decreased, unchanged, and increased risk levels were 15.13%, 81.48%, and 3.39% for 2000–2010 and 0.54%, 94.75%, and 4.71% for 2040–2050. These trends indicated that the proportion of grids with changed risk levels gradually decreased going into the future. This study analyzed the evolutionary trends of LER at the C-C E Zone for the ND and EP scenario. On the whole, the LER for the C-C E Zone showed an upward trend, and the EP scenario was conducive to reducing the risk. These research results can serve as a valuable data reference set for regional landscape optimization and risk prevention and control.

Analysis of Evolving Carbon Stock Trends and Influencing Factors in Chongqing under Future Scenarios

“…This study conducted an analysis of the future evolution trends and key influencing factors of carbon storage in the Chongqing Municipality using the PLUS model, InVEST model, and Geographic Detector model in a multi-model framework. Building upon landuse data from 2000 to 2020 in Chongqing, and referencing relevant literature [12] while considering regional circumstances, the study employed NDVI, slope, elevation, primary rivers, secondary rivers, urban arterial roads, expressways, highways, and other roads as driving factors for land-use changes. Water areas were considered limiting factors for land-use changes.…”

“…The specific simulation steps involved two stages. The first stage used land-use data from 2000 and 2010 as a basis to simulate data for 2010 and 2020, and accuracy analysis was performed using the Kappa coefficient, with a coefficient above 0.75 indicating high consistency, as typically seen in literature [12]. The second stage involved simulating land-use data for 2030, 2040, and 2050 under two scenarios: natural development and ecological conservation.…”

“…The PLUS (Patch-generating Land Use Simulation Model) model, developed by the HPSCIL@CUG laboratory team at the China University of Geosciences in recent years [11], is a land-use-type data simulation software that has demonstrated good results at a larger scale. For instance, Zhu used the PLUS model to conduct ecological risk simulations in the Chengdu-Chongqing Economic Zone (20.6 × 10 4 km 2 ) [12], and Yang performed ecosystem service value simulation in the Guanzhong Plain Urban Agglomeration (10.7 × 10 4 km 2 ) [13]. Therefore, the PLUS model makes it possible to conduct large-scale land-use-type data simulations.…”

Blackland Conservation and Utilization, Carbon Storage and Ecological Risk in Green Space: A Case Study from Heilongjiang Province in China

“…Concerning earlier research techniques, this study built the HLJP ecological risk evaluation model based on the characteristics of the landscape pattern [ 48 , 49 , 50 , 51 , 52 , 53 , 54 ] ( Table 2 ). By the principle of 2–5 times the average area of landscape patches in the study region [ 55 ], the study area was divided at equal intervals into a 20 km × 20 km rectangular grid, and 1273 ecological risk plots were obtained.…”

A Method for Assessing Urban Ecological Resilience and Identifying Its Critical Distance Belt Based on the “Source-Sink” Theory: A Case Study of Beijing

“…where K represents Kappa value, P a is the proportion of correct simulations, P b is the proportion of correct model simulations in the stochastic case, and P c is the proportion of correct simulations in the ideal case, usually defined as 1. The Kappa takes values in the range [−1, 1], and it is usually considered that if the Kappa is higher than 0.75, the model simulation results achieve a high level of agreement with the actual distribution [41].…”