Multi-Scenario Land Use and Carbon Storage Assessment in the Yellow River Delta Under Climate Change and Resource Development

Impact of land use change on carbon storage based on the PLUS–InVEST model: A case study in the urban belt along the Yellow River, China

Land use and land cover (LULC) change in tropical regions can cause huge amounts of carbon loss and storage, thus significantly affecting the global climate. Due to the differences in natural and social conditions between regions, it is necessary to explore the correlation mechanism between LULC and carbon storage changes in tropical regions from a broader geographical perspective. This paper takes Hainan Island as the research object, through the integration of the CA-Markov and Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) models, based on multi-source data, analyses the dynamics of LULC and carbon storage from 1992 to 2019 and the relationship between the two, and predicts future LULC and carbon storage under different scenarios. The results show that (1) the built-up land area of Hainan Island expanded from 103.59 km2 to 574.83 km2 from 1992 to 2019, an increase of 454.91%; the area of cropland and shrubland decreased; and the area of forest increased. (2) Carbon storage showed an upward trend during 1992–2000, and a downward trend during 2000–2019. Overall, LULC changes during 1992–2019 reduced carbon storage by about 1.50 Tg. (3) The encroachment of cropland in built-up land areas is the main reason for the reduction of carbon storage. The conversion of shrubland to forest is the main driving force for increasing carbon storage. The increase and decrease of carbon storage have obvious spatial clustering characteristics. (4) In the simulation prediction, the natural trend scenario (NT), built-up land priority scenario (BP) and ecological priority scenario (EP) reduce the carbon storage of Hainan Island, and the rate of decrease is BP> NT > EP. The cropland priority scenario (CP) can increase the LULC carbon storage, and the maximum increase in 2050 can reach 0.79 Tg. This paper supplements and improves the understanding of the correlation between LULC and carbon storage changes in tropical regions, and can provide guidance for the optimization of LULC structure in tropical regions with high economic development from a low-carbon perspective.

The most extensive carbon reservoir system on Earth is found in the vegetation and soil in terrestrial ecosystems, which are essential to preserving the stability of ecosystems. Land use/cover change (LUCC) patterns in terrestrial ecosystems significantly impact carbon storage (CS). Therefore, it is imperative to investigate the relationship between LUCC and CS to coordinate regional ecological conservation and industrial development. In this study, the characteristics of spatial and temporal changes in land use and CS in the Yanqi Basin from 2000 to 2020 were revealed using the PLUS (patch-generating land use simulation) model and the CS module of the InVEST (Integrated Valuation of Ecosystem Services and Tradeoffs) model. This study also predicted the spatial and temporal evolution of CS and the response mechanism of the Yanqi Basin from four scenarios—natural development scenario (NDS), ecological protection scenario (EPS), cropland protection scenario (CPS), and urban development scenario (UDS) for the years 2030, 2040, and 2050. This study shows the following: (1) Between 2000 and 2020, the Yanqi Basin witnessed an expansion in cropland and construction land, the order of the land use dynamic degree which is as follows: construction land > cropland > woodland > unused land > water > grassland. At the same time, the CS exhibited a trend of growth that was followed by a decline, a cumulative decrease of 3.61 Tg. (2) Between 2020 and 2050, woodland, grassland, and unused land decreased under the NDS and UDS. Meanwhile, grassland and woodland showed an expanding trend, and there was a decrease in cropland and construction land under the EPS; the CPS projected an increase in cropland to 3258.06 km2 by 2050. (3) CS under the UDS is always the lowest, and CS under the EPS is the highest; moreover, by 2050, CS under the EPS is projected to increase by 1.18 Tg compared with that under the UDS. The spatial distribution of CS shows a high value in the western part of the region and a low value in the eastern part of the region, which is more in line with the historical spatial distribution. (4) The development of land by human activities is one of the major factors leading to the change of CS. The direct cause of the decrease in CS is the transformation of large areas of cropland and woodland into construction land. Therefore, woodlands must be protected to improve CS and prevent ecological degradation. At the same time, future land use planning in the Yanqi Basin needs to limit the conversion rate of various types of land, control the construction land, optimize the urban pattern, improve the regional CS level, adhere to the concept of striving to achieve carbon neutrality, and realize the sustainable development of the region to provide scientific suggestions for carrying out macro-decision making regarding land use planning in arid areas.

Land use and land cover change (LUCC) significantly influences the dynamics of carbon storage in thin terrestrial ecosystems. Investigating the interplay between land use alterations and carbon sequestration is crucial for refining regional land use configurations, sustaining the regional carbon balance, and augmenting regional carbon storage. Using land use data from the Pearl River Delta Urban Agglomeration (PRDUA) from 2010 to 2020, this study employed PLUS-InVEST models to analyze the spatiotemporal dynamics of land use and carbon storage. Projections for the years 2030, 2040, and 2050 were performed under three distinct developmental scenarios, namely, natural development (ND), city priority development (CPD), and ecological protection development (EPD), to forecast changes in land use and carbon storage. The geographic detector model was leveraged to dissect the determinants of the spatial and temporal variability of carbon storage, offering pertinent recommendations. The results showed that (1) during 2010–2020, the carbon storage in the PRDUA showed a decreasing trend, with a total decrease of 9.52 × 106 Mg, and the spatial distribution of carbon density in the urban agglomeration was imbalanced and showed an overall trend in increasing from the center to the periphery. (2) Clear differences in carbon storage were observed among the three development scenarios of the PRDUA between 2030 and 2050. Only the EPD scenario achieved an increase in carbon storage of 1.10 × 106 Mg, and it was the scenario with the greatest potential for carbon sequestration. (3) Among the drivers of the evolution of spatial land use patterns, population, the normalized difference vegetation index (NDVI), and distance to the railway had the greatest influence on LUCC. (4) The annual average temperature, annual average rainfall, and GDP exerted a significant influence on the spatiotemporal dynamics of carbon storage in the PRDUA, and the interactions between the 15 drivers and changes in carbon storage predominantly manifested as nonlinear and double-factor enhancements. The results provide a theoretical basis for future spatial planning and achieving carbon neutrality in the PRDUA.

Assessment and prediction of carbon storage based on land use/land cover dynamics in the coastal area of Shandong Province

Land Use and Cover Change (LUCC) has emerged as a primary driver of terrestrial carbon storage changes. However, the contributions of LUCC to Above-Ground Carbon (AGC) storage in subtropical forests remain unclear due to the complex and diverse LUCC trajectory. Quantitative assessment of the impact of different LUCC trajectories on carbon storage is essential for regional carbon cycle mechanisms. Therefore, this study focuses on Zhejiang Province, a representative subtropical forest region in China, to accurately assess the contribution of LUCC to AGC storage changes from 1984 to 2019. We first mapped the land cover patterns using the random forest and spatiotemporal filtering algorithm and then applied these patterns to drive an optimized BIOME-BGC model to simulate the spatiotemporal distribution of AGC density. Finally, the LUCC trajectories were classified into three categories: afforestation, deforestation, and forest type transformations. Their contributions to AGC changes were isolated and analyzed through the trajectory analysis. The results demonstrated that the forest area of Zhejiang Province increased from 5.35 × 106 ha to 6.83 × 106 ha (+27.66%) and the total forest AGC storage increased from 80.52 Tg C to 124.16 Tg C (+54.19%) between 1984 and 2019. The increase in forest AGC due to LUCC amounted to 31.26 Tg C, contributing 71.63% to the total. Specifically, the afforestation, deforestation, and forest type transformations contributed 82.37%, −17.27%, and 6.53% to the change in AGC, respectively. Overall, the afforestation within the LUCC trajectories was the primary contributing factor to the growth of forest AGC in Zhejiang Province from 1984 to 2019. This study obtained accurate LUCC and AGC data, clarifying the contribution of different LUCC trajectories and providing a better understanding of the responses of the forest carbon storage to LUCC dynamics.

Guaranteeing the ecological security of the Dongting Lake Basin is of paramount importance for national-scale programs, such as the Yangtze River Economic Belt and aquatic conservation projects. Within this framework, carbon storage and its determining drivers act as essential indicators of regional ecological stability. However, the historical trajectory of carbon pools and their response to future multi-scenario land-use transitions remain insufficiently understood. Therefore, this study aims to quantify the spatiotemporal evolution of carbon storage in the Dongting Lake Basin from 2000 to 2020 and project its future dynamics under diverse development pathways. This study, utilizing land use data from 2000 to 2020 and the carbon density database of the Dongting Lake Basin, assessed land use changes over two decades and determined the spatiotemporal distribution of carbon storage. Additionally, using 17 driving factors and various spatial policies, the study projected the land use and land cover changes (LUCC) for 2030 under four scenarios: natural development, ecological protection, economic development, and planned development. The spatiotemporal distribution of carbon storage and its response mechanisms were analyzed for each scenario. The results showed that carbon storage was directly impacted by LUCC, with an overall “decrease-increase-decrease” trend from 2000 to 2020, resulting in a net increase of 3.685 × 106 t. By 2030, the changes in carbon storage under the natural development, ecological protection scenario, economic development, and planned development scenarios were projected to be −1.008 × 107 t, 1.276 × 107 t, 3.292 × 108 t, and −1.200 × 105 t, respectively. Notably, the ecological protection scenario showed a significant positive growth in carbon storage, primarily driven by an increase in forest and wetland areas. Additionally, the spatial distribution of carbon storage exhibited a pattern of “high in the west and low in the east”. These results imply that to achieve the “Dual Carbon Strategy”, future land use planning in the Dongting Lake Basin should prioritize ecological protection and planned development models, including strict control of construction land expansion, increasing ecological land area, and enhancing carbon storage.

With the rapid development of the social economy, human activities have had a severe impact on the environment. The global climate issue caused by CO2 emissions has attracted the attention of various countries around the world, and reducing CO2 emissions is urgent. This article simulates the changes in carbon storage in Anhui Province from 2030 to 2070 based on SSP1-2.5, SSP2-4.5, and SSP5-5.8 scenarios. First, based on the land use data of Anhui Province in 2010, the PLUS model was used to simulate the land use data of 2015, and the accuracy of the simulation results was verified against real data. Then, the land use data of Anhui Province were simulated in the future period from 2030 to 2070 under different SSP scenarios. Finally, based on the InVEST model, the spatiotemporal changes in future carbon storage were calculated. The research showed that, during the period of 2030 to 2070, the spatial distribution of carbon storage in Anhui Province under three scenario simulations generally showed a distribution pattern of high carbon storage in the north and south, and low carbon storage in the central region. Under the SSP1-2.6 scenario, Anhui Province’s carbon storage decreased by 0.33 million tons, a decrease of 0.029%. Under the SSP2-4.5 scenario, carbon storage increased by 0.25 million tons, an increase of 0.021%. Under the SSP5-8.5 scenario, carbon storage decreased by 1.54 million tons, a decrease of 0.133%. The reasons for the changes in carbon storage were related to the areas of arable land, forest land, and grassland. This study can provide a reference for future low-carbon land use planning.

Land use/cover change （LUCC） is an important factor affecting regional carbon storage. It is of great significance to study the relationship between LUCC and carbon storage for optimizing land management and improving ecological environment. The land use status of Henan Province has changed significantly in recent years. Based on land cover data and combined with InVEST and PLUS model， this study analyzed the spatio-temporal evolution of LUCC in Henan Province from 2005 to 2020， as well as the development trend of LUCC and carbon storage under the natural development scenario （Q1）， ecological protection scenario （Q2）， and urban development scenario （Q3）. The results show that： ① The total carbon storage of Henan Province decreased 87.47×106 t from 2005 to 2020， and the carbon storage of different land use types was as follows： cropland > forest > grassland > urban area > water area > unused land， which was consistent with the size of land types. ② In the future three scenarios， the area of six land use types in Henan Province was as follows： cropland > forest > urban area > water area > grassland > unused land. The construction land area increased obviously in Q1 and Q3 compared with that in Q2， the grassland increased obviously in Q2 compared with that in Q1 and Q3， and the increase mainly occurred in the central and northern parts of Henan Province. ③ The carbon storage under three scenarios in Henan Province showed a trend of "Q1 decreasing- Q2 increasing- Q3 decreasing" in 2035， indicating that the regional carbon storage will decrease by 12.80×106 t compared with that in 2020 under the condition of good ecological environment. Furthermore， the larger carbon storage was distributed in the western， northern， and southern provincial boundaries of Henan Province. There was a good consistency between LUCC and carbon storage change in Henan Province. Therefore， optimizing the spatial distribution of land use and formulating reasonable policies to protect grassland and forest will help to improve regional carbon reserves. This study can provide scientific reference for Henan Province to further implement sustainable development and achieve the goal of "double carbon".

Contribution of multi-objective land use optimization to carbon neutrality: A case study of Northwest China

Effects of land use/cover change on carbon storage between 2000 and 2040 in the Yellow River Basin, China

Introduction: The carbon storage service of ecosystems in ecologically fragile areas is highly sensitive to regional land use/land cover (LULC) changes. Predicting changes in regional carbon storage under different LULC scenarios is crucial for land use management decisions and exploring carbon sink potential. This study focuses on the Luan River Basin, a typical ecologically fragile area, to analyze the impact of LULC changes on carbon storage.Methods: The PLUS-InVEST model was employed to simulate LULC patterns for the year 2030 under three scenarios: natural development, cropland protection and urban development, and ecological protection. The model projected the future carbon sink potential of the basin under these scenarios.Results: From 2000 to 2020, carbon storage showed a trend of decrease followed by an increase. By 2030, compared to 2020, carbon storage is projected to increase by 16.97% under the ecological protection scenario and decrease by 22.14% under the cropland protection and urban development scenario. The increase in carbon storage was primarily due to the conversion of cropland and grassland to forestland, while the decrease was mainly associated with the conversion of forestland to grassland and cropland, and the transformation of grassland to cropland and construction land. In the potential LULC scenarios of 2030, certain regions within the basin exhibited unstable carbon sink potential, strongly influenced by LULC changes. These areas were predominantly characterized by artificially cultivated forests, shrubs, and agricultural land. Implementing appropriate forest management measures and optimizing agricultural land management practices are essential to enhance carbon sink potential in these regions. Population density, annual average temperature, and DEM (Digital Elevation Model) were the dominant factors driving the spatial variation of carbon sink potential in the Luan River Basin.Discussion: The research results provide a theoretical basis for rational planning of land use and the enhancement of carbon sink potential in ecologically fragile regions.

Analyzing the current trends and causes of carbon storage changes and accurately predicting future land use and carbon storage changes under different climate scenarios is crucial for regional land use decision-making and carbon management. This study focuses on Beijing as its study area and introduces a framework that combines the Markov model, the Patch-based Land Use Simulation (PLUS) model, and the Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) model to assess carbon storage at the sub-district level. This framework allows for a systematic analysis of land use and carbon storage spatiotemporal evolution in Beijing from 2000 to 2020, including the influence of driving factors on carbon storage. Moreover, it enables the simulation and prediction of land use and carbon storage changes in Beijing from 2025 to 2040 under various scenarios. The results show the following: (1) From 2000 to 2020, the overall land use change in Beijing showed a trend of “Significant decrease in cropland area; Forest increase gradually; Shrub and grassland area increase first and then decrease; Decrease and then increase in water; Impervious expands in a large scale”. (2) From 2000 to 2020, the carbon storage in Beijing showed a “decrease-increase” fluctuation, with an overall decrease of 1.3 Tg. In future carbon storage prediction, the ecological protection scenario will contribute to achieving the goals of carbon peak and carbon neutrality. (3) Among the various driving factors, slope has the strongest impact on the overall carbon storage in Beijing, followed by Human Activity Intensity (HAI) and Nighttime Light Data (NTL). In the analysis of carbon storage in the built-up areas, it was found that HAI and DEM (Digital Elevation Model) have the strongest effect, followed by NTL and Fractional Vegetation Cover (FVC). The findings from this study offer valuable insights for the sustainable advancement of ecological conservation and urban development in Beijing.

Response and multi-scenario prediction of carbon storage to land use/cover change in the main urban area of Chongqing, China

This study aimed to investigate the impact of spatiotemporal changes in land use on ecosystem carbon storage. The study analyzed the spatiotemporal changes in carbon storage in the study area based on land use data from five periods (1985, 1995, 2005, 2015, and 2020) using the InVEST model. The PLUS model was used to predict land use changes in the study area under four different scenarios (natural development, farmland protection, ecological protection, and double protection of farmland and ecology) in 2035, and the ecosystem carbon storage under different scenarios was estimated. The results of the study indicated that the farmland in the area under investigation had been decreasing consistently from 1985 to 2020, with a more rapid rate of change observed between 2015 and 2020. During this period, the overall dynamic attitude towards land use reached 34.62 %. Additionally, the carbon storage in the area showed a decreasing trend over the years, with a decrease of 1.55×105 t from 1985 to 2020. Between 2005 and 2015, the carbon storage showed a decrease of 1.22×105 t, with an average annual decrease of 1.22×104 t. The areas with higher carbon storage were located in the eastern part of the study area, whereas areas with lower carbon storage were found in the central and northwestern parts. Although the proportion of carbon storage in farmland decreased from 66.89 % to 57.73 %, farmland remained the most important carbon pool in the study area. The conversion of other land use types to grassland and forestland was advantageous for increasing ecosystem carbon storage. Finally, the study projected that by 2035, the carbon storage in the natural development scenario, the farmland protection scenario, the ecological protection scenario, and the dual protection scenario would be 81.77×105, 82.45×105, 82.82×105, and 82.51×105 t, respectively.