Projections of land use change and habitat quality assessment by coupling climate change and development patterns

Impacts of climate and land use change on terrestrial carbon storage: A multi-scenario case study in the Yellow River Basin (1992-2050)

Currently, socioeconomic development and climate change pose new challenges to the assessment and management of terrestrial carbon storage (CS). Accurate prediction of future changes in land use and CS under different climate scenarios is of great significance for regional land use decision-making and carbon management. Taking the Yellow River Basin (YRB) in China as the study area, this study proposed a framework integrating the land use harmonization2 (LUH2) dataset, the patch-generating land use simulation (PLUS) model, and the integrated valuation of ecosystem services and trade-offs (InVEST) model. Under this framework, we systematically analyzed the spatiotemporal evolution characteristics of land use and their impact on CS in the YRB from 1992 to 2050. The results showed that (1) CS was highest in forestland and lowest in construction land, with a spatial distribution of high in the south and low in the north. From 1992 to 2020, construction land, forestland, and grassland increased while cropland decreased, reducing the total CS by 74.04 Tg. (2) From 2020 to 2050, under SSP1-2.6 scenario, forestland increased by 158.87 %; under SSP2-4.5 scenario, unused land decreased by 65.55 %; and under SSP5-8.5 scenario, construction land increased by 13.88 %. By 2050, SSP1-2.6 scenario exhibited the highest CS (8105.25 Tg), followed by SSP2-4.5 scenario (7363.61 Tg), and SSP5-8.5 scenario was the lowest (7315.86 Tg). (3) Forestland and construction land were the most critical factors affecting the CS. Shaanxi and Shanxi had the largest CS in all scenarios, and Qinghai had a huge carbon sink potential under SSP1-2.6 scenario. Scenario modeling demonstrated that future climate and land-use changes would have significant impacts on terrestrial CS in the YRB, and green development pathways could strongly contribute to meeting the dual‑carbon target. Overall, this study provides a scientific basis for promoting low-carbon development, land-use optimization, and ecological civilization construction in YRB, China.

Future land use prediction and optimization strategy of Zhejiang Greater Bay Area coupled with ecological security multi-scenario pattern

The land use changes driven by human activities press a incredible menace to zonal ecological security. As the most active urban cluster, the uncontrolled expansion of cities in the bay area exerts enormous pressure on the ecosystem. Therefore, from the perspective of ecological conservation, exploring future land use optimization patterns and spatial structure is extremely essential for the long-term thriving of the bay area. On this basis, this research integrated the System Dynamics model (SD) as the quantity forecast model and the PLUS model as the spatial emulation model and established the Land Use/Cover Change (LUCC) Simulation Framework by setting the constraints of Ecological Security Multi-Scenario Patterns (ESMP). By setting four scenarios in future, that is, Business As Usual (BAU), Priority of Ecological Protection (PEP), Balanced Development Scenario (BD), and Priority of Urban development (PUD), this research predicts LUCC in the Zhejiang Greater Bay Area (ZGBA) in 2035 and explored land use optimization patterns. The results indicate that by 2035, under the scenarios of BAU, BD, and PUD, the construction land will observably grow by 38.86%, 19.63%, and 83.90%, respectively, distributed mainly around the Hangzhou Bay Area, Taizhou Bay Area, and Wenzhou Bay Area, primarily achieved by sacrificing ecologically sensitive lands such as forests to achieve regional high economic growth. Under PEP, the growth of construction land retards, and forest experiences net growth (11.27%), with better landscape connectivity and more cohesive patches compared to other scenarios. Combining regional planning and analysis at the city scale, Hangzhou Bay area (Hangzhou, Huzhou, Jiaxing, Shaoxing, Ningbo) can adopt the BD development scenario, while Zhoushan, Taizhou, Wenzhou and Fuyang County of Hangzhou can adopt the PEP development scenario. This research furnishes a novel mechanism for optimizing land use pattern in ecological security perspective and offers scientific guidance for land resource management and spatial planning in ZGBA.

Exploring the supply and demand imbalance of carbon and carbon-related ecosystem services for dual‑carbon goal ecological management in the Huaihe River Ecological Economic Belt

The measurement of carbon and carbon-related ecosystem services (CCESs) has garnered considerable global attention, primarily due to dual‑carbon goals, which are crucial for the rational allocating of ecosystem service (ES) resources and the enhancement of terrestrial carbon sinks. This study developed a novel research framework on CCESs to quantitatively measure carbon storage (CS), food production (FS), habitat quality (HQ), soil conservation (SC), and water yield (WY), and examined the spatiotemporal patterns of the supply-demand and trade-off/synergy processes related to CCESs in the Huaihe River Ecological Economic Belt (HREEB). The findings are as follows: (1) From 2000 to 2020, the supply-demand of the CCESs generally increased, except for carbon storage and food demand. Overall, the supply level of the CCESs exceeds the demand level, with a median ratio of supply and demand ratio (ESDR) of 1.13. (2) During the study period, the synergy relationship of the CCESs is mainly determined by the supply side of the CS-HQ and CS-SC, while on the demand side, it is determined by the CD- FD. And the ESDR of all C-related ecosystem services showed a significant synergy strengthening with CS in the HREEB. (3) Spatially, "high-low" spatial matching of the ESDR decreased, suggesting a gradual reduction in the spatial mismatch of CCESs. (4) We identified seven ecological functional zones and proposed corresponding strategies for promoting ecological management. Our research emphasized the spatiotemporal patterns of supply and demand imbalance in CCESs and the spatial optimization paths of trade-offs/synergies, providing valuable insights for achieving regional dual‑carbon goals.

A simulation and risk assessment framework for water-energy-environment nexus: A case study in the city cluster along the middle reach of the Yangtze River, China

In the Anthropocene, there is a strong interlinkage among water, energy, and the environment. The water-energy-environment nexus (WEEN) has been vigorously advocated as an emerging development paradigm and a global research agenda. Based on the nexus concept, a framework for the WEEN complex system simulation and risk assessment is developed. The three metropolitan areas of the city cluster along the middle reaches of the Yangtze River (CCMRYR) are taken as the objects. Regional policies are combined with generic shared socio-economic pathways (SSPs) to form a localized SSPs suitable for the research region. The dynamic simulation of the WEEN complex system and the risk analysis are carried out with the combination of system dynamics models and copula functions. Results show that: There are obvious differences in water utilization, energy consumption, air pollutant emissions, and water pollutant emissions among the three metropolitan areas. The issue of high carbon intensity in the Wuhan Metropolitan Coordinating Region needs to be emphasized and solved from the perspective of optimizing the industrial structure. Adhering to current development patterns, there will be successive peaks in water utilization, energy consumption, and carbon emissions in Wuhan, Dongting Lake, and Poyang Lake Metropolitan Coordinating Region by 2030, leading to high synergy risks at the systemic level, with maximum values of 0.84, 0.85, 0.62, respectively. A development path based on conservation priorities indicates that future policymaking needs to prioritize a resource-saving and pollution-control development pattern directed by technological upgrading against the backdrop of scarce natural resource endowments. The localized SSPs are a beneficial extension that enriches the narrative of regional-scale SSPs. The evolutionary trajectories and risk assessments of WEEN complex systems under different localized SSPs provide a sweeping insight into the consequences of policy decisions, thus enabling policymakers to appraise policy rationality and implement appropriate corrective measures.

Thriving arid oasis urban agglomerations: Optimizing ecosystem services pattern under future climate change scenarios using dynamic Bayesian network

The effects of global climate change and human activities are anticipated to significantly impact ecosystem services (ESs), particularly in urban agglomerations of arid regions. This paper proposes a framework integrating the dynamic Bayesian network (DBN), system dynamics (SD) model, patch generation land use simulation (PLUS) model, and the Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) model for predicting land use change and optimizing ESs spatial patterns that is built upon the SSP-RCP scenarios from CMIP6. This framework is applied to the oasis urban agglomeration on the northern slope of the Tianshan Mountains in Xinjiang (UANSTM), China. The findings indicate that both the SD model and PLUS model can accurately forecast the distribution of future land use. The SD model shows a relative error of less than 2.32%, while the PLUS model demonstrates a Kappa coefficient of 0.89. The land use pattern displays obvious spatial heterogeneity under different climate scenarios. The expansion of cultivated land and construction land is the main form of land use change in UANSTM in the future. The DBN model proficiently simulates the interactive relationships between ESs and diverse factors. The classification error rates for net primary productivity (NPP), habitat quality (HQ), water yield (WY), and soil retention (SR) are 20.04%, 3.47%, 4.45%, and 13.42%, respectively. The prediction and diagnosis of DBN determine the optimal ESs development scenario and the optimal ESs region in the study area. It is found that the majority of ESs in UANSTM are predominantly influenced by natural factors with the exception of HQ. The socio-economic development plays a minor role in such urban agglomerations. This study offers significant insights that can contribute to the fields of ecological protection and land use planning in arid urban agglomerations worldwide.

The impact of teleconnections of built-up land on regional carbon burden under the shared socio-economic pathways

The expansion of built-up land is currently being increasingly triggered by remote demand, thus disturbing the local process of carbon neutrality significantly. It is meaningful to understand the relations between regional development and carbon balance. To this end, we combine the multi-regional input-output model with the land system cellular automata model for potential effects (LANDSCAPE) to illustrate the impact that regional development has on the carbon burden. The results show that the expansion of built-up land results in a regional carbon burden through taking over ecological land and generating carbon emissions, to which the manufacturing industry land is the largest contributor. Regionally, developed regions exert the greatest influences on the changes in the regional carbon burden, mainly because the promotion of their development leads to the expansion of built-up land in all regions. Developing regions can impact undeveloped regions and themselves, while it is hard for undeveloped regions to change the regional carbon burden due to their low capacity to externally drive the expansion of built-up land. Meanwhile, the continuing development of developed regions exerts great pressure on carbon neutrality in both developing and undeveloped regions as they expand the "high-quality" built-up land themselves, which means that regional development may lead to changes in the carbon burden of regions which are less developed.

Dynamic simulation of land use change and habitat quality assessment under climate change scenarios in Nanchang, China

Investigating habitat quality under different climate scenarios holds significant importance for sustainable land resource management and ecological conservation. In this study, considering Nanchang as a case study, a coupled patch-generating land use simulation (PLUS) and system dynamics (SD) model was employed in the simulation and prediction of land usage under shared socioeconomic pathway (SSP) and representative concentration pathway (RCP) scenarios. To assess the habitat quality in Nanchang from 2000 to 2020 and in 2030 under three diverse climate scenarios, we used the Integrated Valuation of Ecosystem Services and Trade-offs (InVEST) model to analyze spatial and temporal changes. The findings indicate that the regions of forest land, cultivated land, and grassland in Nanchang City will dramatically decrease by 2030, the construction land will rapidly expand, and the fluctuations in the unutilized land and water area will be minimal. Additionally, the habitat quality declined from 2000 to 2020, and its spatial distributions changed. Zones having a high overall habitat quality were distributed in the mountains, hills, and lake areas, whereas those with relatively low quality were found in cultivated and urban areas. Under three climate scenarios, in 2030, the habitat quality index for Nanchang City will show a decreasing trend, mainly owing to areas with an index of 0.3-0.5 transitioning to <0.3. Considering each scenario, the degree of habitat degradation increased in the order SSP585>SSP245>SSP119. The findings of this study will inform high-quality development and biodiversity conservation in Nanchang City.

Land use and habitat quality change in the Yellow River Basin: A perspective with different CMIP6-based scenarios and multiple scales

Studying the spatial distribution of land use/land cover (LULC) and habitat quality (HQ), influenced by both climate change and socio-economic factors, holds immense importance for fostering ecological sustainability. The previous scale setting was based on changes in granularity and division of spatial ranges, without considering the differences in land quantity structure and spatial expansion under different spatial ranges. Therefore, this study is based on climate and economic data at different spatial scales to determine the various land demands of provinces (YRB-P) and integration of provinces (YRB-I) in the Yellow River Basin, and to limit the expansion of LULC in corresponding regions. At the same time, we have also established three future scenarios representing different development speeds based on the latest path of shared socio-economic development in CMIP6. We found exhibit significant characteristics in ecological responses under combinations of different scales and scenarios. Shandong and Henan Provinces are the main gathering (38.7-41.7%, 24.1-26.5%) and expansion (68.54-85.99 × 102km2, 18.89-34.12 × 102km2) provinces of built-up land under the YRB-P scale, and their HQ (0.260-0.397) are significantly lower than the average HQ (0.619-0.654). Forest land, grassland, and high value regions of HQ show "45°" distribution at two scales, with high and low values clearly clustered (Moran's I is 0.5440-0.580). The HQ evolution region is larger and more dispersed at the YRB-P scale, but accumulates in local areas at the YRB-I scale. In addition, the highest and lowest HQ mean values appear under the low speed development scenario at the YRB-P scale (0.721) and the rapid development scenario at the YRB-I scale (0.689), respectively. This study helps decision-makers control different scales and development scenarios to improve the ecological level of the study area.

Spatiotemporal evolution of land cover changes and landscape ecological risk assessment in the Yellow River Basin, 2015-2020

The Yellow River Basin (YRB), which has faced severe ecological issues since ancient times, is one of the largest and most difficult-to-govern basins in the world. Recently, all provincial governments within the basin have individually enacted a series of measures to protect the Yellow River; however, the lack of central governance has inhibited efforts. Since 2019, the government has comprehensively managed the YRB, improving the governance to unprecedented levels; however, evaluations of the YRB's overall ecological status remain lacking. Using high-resolution data from 2015 to 2020, this study illustrated major land cover transitions, evaluated the correlated overall ecological status of the YRB via the landscape ecological risk index, and analyzed the relationship between risk and landscape structure. The results showed that the (1) main land cover types in the YRB in 2020 are farmland (17.58%), forestland (31.96%), and grassland (41.42%), with urban land accounting for 4.21%. Some social factors were significantly related to changes in major land cover types (e.g., from 2015 to 2020, forest and urban lands have increased by 2.27% and 10.71%, grassland and farmland decreased by 2.58% and 0.63%, respectively). (2) Landscape ecological risk improved, albeit with fluctuations (high in the northwest, low in the southeast). (3) Ecological restoration and governance were imbalanced since no obvious changes were observed in the western source region of the Qinghai Province (Yellow River). (4) Finally, positive impacts of artificial re-greening showed slight lags as the detected improvements in NDVI were not recorded for approximately 2 years. These results can facilitate environmental protection and improve planning policies.

Spatiotemporal Analysis of the Coupling Relationship between Habitat Quality and Urbanization in the Lower Yellow River

Natural habitats are damaged by human interference to varying degrees during the urbanization process, which can impede a region's high-quality development. In this study, we examined the spatial-temporal evolution characteristics of habitat quality and urbanization in the Lower Yellow River from 2000 to 2020 using the integrated valuation of ecosystem services and tradeoffs (InVEST) model and the comprehensive indicator method. We also evaluated the coupling relationship between the habitat quality and urbanization using the coupling coordination degree model. The findings indicate the following aspects: (1) Between 2000 and 2020, the Lower Yellow River's habitat quality was typically mediocre, with a steady declining trend. The majority of cities displayed a trend toward declining habitat quality. (2) Both the urbanization subsystem and the urbanization level in 34 cities have demonstrated a consistent growth tendency. The urbanization level is most affected by economic urbanization among the subsystems. (3) The coupling coordination degree have revealed an ongoing trend of growth. In most cities, the relationship between habitat quality and urbanization has been evolving toward coordination. The results of this study have some reference value for ameliorating the habitat quality of the Lower Yellow River and solving the coupling coordination relationship between habitat quality and urbanization.

Spatial pattern evolution and prediction scenario of habitat quality in typical fragile ecological region, China: A case study of the Yellow River floodplain area

The Yellow River basin is an important area for China to implement ecological protection policies. Studying the habitat quality of the Yellow River floodplain area is of great significance to the ecological security and sustainable development of the entire basin. This study primarily investigated the spatial pattern of habitat quality in the Yellow River floodplain area from 2000 to 2020, then, we also simulated changes of habitat quality in 2025-2035 and analyzed the influencing factors by coupling the PLUS (Patch-generating Land Use Simulation) model, InVEST (Integrated Valuation of Ecosystem Services and Trade-offs) model and RF (Random Forest) model. The results showed that:(1) From 2000 to 2020, cultivated land and build-up land constituted an important part of the Yellow River floodplain area, and the growth rate of build-up land was fast. (2) We also found that the ecological land (forest land, grassland, waterbody) had a higher contribution value to the habitat quality, while the build-up land had a lower contribution value to the habitat quality. (3) Overall, the habitat quality of the floodplain area showed a degradation trend from 2000 to 2020. In addition, the regions with low habitat quality accounted for the major proportion. (4) Based on the calculation results of the Random Forest (RF) model, we found that topographical relief (TR) and land use intensity (LUI) were the two most important factors affecting habitat quality of the floodplain area. (5) According to the four scenarios from 2025 to 2035, it is found that the habitat quality level would be the highest under the ecological protection scenario, while under the urban development scenario its level would be the lowest. This study attempts to combine the RF model with PLUS model to improve the objectivity and accuracy of the future prediction scenario of habitat quality, which can provide scientific reference for ecological governance and policy formulation in the Yellow River floodplain area.

Spatial–temporal evolution characteristics of land use and habitat quality in Shandong Province, China

To explore the sustainable mechanism of land use and habitat quality, the present study examined the land cover data of Shandong Province from 1980 to 2020 to understand the spatial–temporal evolution characteristics of land use. The “Integrated Valuation of Environmental Services and Trade-off” (InVEST-HQ) model and spatial auto-correlation model were further employed to evaluate the habitat quality and analyze the relationship between its spatial distribution pattern and land use type. Our results suggested that cultivated land was the dominant land use type in Shandong Province from 1980 to 2020. During this period, the area of water and URL (urban and rural industrial and mining residential land) were gradually increased, while other land types decreased progressively. Political and socio-economic factors were the dominant factors for the evolution of land use types, which exhibited significant stage variation characteristics, and the most drastic change was observed from 2010 to 2020. We further found that habitat quality in Shandong Province was dominated by moderate degradation, whose degree of degradation was positively correlated with the degree of land use development. Moreover, the average habitat quality decreased obviously over the past 40 years, and the fastest decreased period was similar to the phase change characteristics of land use types. In addition, habitat quality was significantly clustered in spatial distribution. Hot spots (high-value areas) were mainly natural ecosystems, while cold spots (low-value areas) were mainly ecosystems that were significantly affected by human activities, such as cultivated land and URL. Our findings suggest that administrators should formulate differentiation policies, solve the development dilemma of low-level habitat quality areas and build land space security pattern to promote the ecological quality.