Ecosystem Services Model Research Articles

Investing in nature can improve equity and economic returns

Sustainable development requires jointly achieving economic development to raise standards of living and environmental sustainability to secure these gains for the long run. Here, we develop a local-to-global, and global-to-local, earth-economy model that integrates the Global Trade Analysis Project (GTAP)-computable general equilibrium model of the economy with the Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) model of fine-scale, spatially explicit ecosystem services. The integrated model, GTAP-InVEST, jointly determines land use, environmental conditions, ecosystem services, market prices, supply and demand across economic sectors, trade across regions, and aggregate performance metrics like GDP. We use the integrated model to analyze the contribution of investing in nature for economic prosperity, accounting for the impact of four important ecosystem services (pollination, timber provision, marine fisheries, and carbon sequestration). We show that investments in nature result in large improvements relative to a business-as-usual path, accruing annual gains of $100 to $350 billion (2014 USD) with the largest percentage gains in the lowest-income countries. Our estimates include only a small subset of ecosystem services and could be far higher with inclusion of more ecosystem services, incorporation of ecological tipping points, and reduction in substitutability that limits economic adjustments to declines in natural capital. Our analysis highlights the need for improved environmental-economic modeling and the vital importance of integrating environmental information firmly into economic analysis and policy. The benefits of doing so are potentially very large, with the greatest percentage benefits accruing to inhabitants of the poorest countries.

Analysis of Spatial and Temporal Variations in Ecosystem Service Functions and Drivers in Anxi County Based on the InVEST Model

Background: Exploring the spatial and temporal evolution patterns of regional ecosystem service functions and their main drivers can provide effective support for formulating regional ecological conservation policies and coordinating sustainable economic–ecological development. Methods: This study quantifies the service functions of the water production, soil conservation, carbon storage, habitat quality, and net primary productivity (NPP) in the study area based on the Integrated Valuation of Ecosystem Services and Trade-offs (InVEST) model and the Carnegie–Ames–Stanford Approach (CASA) model and constructs a comprehensive index for ecosystem services (CES) based on the analytic hierarchy process (AHP) to reflect the total supply of various ecosystem services spatially and explore the main driving mechanisms of their spatial variation. The main driving mechanisms of the spatial variation were investigated. Results: (1) Water production in the study area from 2010 to 2020 showed a trend of increasing before decreasing, soil retention showed a trend of continuously decreasing, carbon storage and biotope quality showed a trend of decreasing before increasing, and the NPP showed a trend of continuously increasing. (2) The mean CES of the study area from 2010 to 2020 (0.5398, 0.5763, 0.5456) showed a trend of increasing before decreasing. The improvement areas were mainly concentrated in the western, southwestern, and northeastern parts of the study area, and the degraded areas were mainly distributed in the southeast and northwest. (3) The fit of the geographically weighted regression (GWR) was higher than that of the ordinary least squares (OLS) in all the periods, and the main driving factors affecting the spatial variation in the CES were the NDVI and tea plantation area (T-Area). Conclusion: This study constructed the CES model, explored the regional CES spatiotemporal evolution pattern and its main driving mechanism, and provided a reference basis for promoting the high-quality development of specialized tea regions.

Assessment of soil- and water-related ecosystem services with coupling the factors of climate and land-use change (Example of the Nitra region, Slovakia)

Climate and land use change can profoundly impact the provision of ecosystem services (ES) over time, particularly in the landscape of open fields along with growing urbanization and rising demand for space, food and energy. Policymakers are keen on knowing the combined effects of climate and land use change on ESs as a critical issue in human well-being. However, deep knowledge of how to identify these relationships is still lacking. This research aims to undertake a comprehensive assessment of soil- and water-related ES, and improvement in understanding how they are affected by climate and land use change. We applied the Integrated Valuation of Ecosystem Services and Trade-offs model for four ES (soil retention, nutrient delivery ratio, carbon storage, and water yield) for the years 2000 and 2018 in the Nitra region, Slovakia. We investigated the spatial and temporal changes in ES provision and determined the hotspots and coldspots of multiple ES. We found that soil retention, water yield, and carbon storage display a rising trend while the nutrient delivery ratio showed a decreasing trend over the past 18 years. Although all the mentioned services mainly attributed to land use change, the relative contribution of climate change was not deniable. Forests in the north and east and distributed urbanization and agriculture are the hotspots and coldspots for all ESs, respectively. Our results, in terms of determining the relative importance of land use and climate change and identifying the sensitive areas of ES provision, provide a scientific basis for ecosystem conservation and management priority setting at the local and regional levels.

TP Concentration Inversion and Pollution Sources in Nanyi Lake Based on Landsat 8 Data and InVEST Model

Phosphorus is a limiting nutrient in freshwater ecosystems. Therefore, it is of great significance to use remote sensing technology to estimate the Total phosphorus (TP) concentration in the lake body and identify the contribution of TP inflow load in the surrounding area of the lake body. In this study, two main frameworks (empirical method and machine learning algorithm) for TP estimation are proposed and applied to the development of the Nanyi Lake algorithm. Based on the remote sensing data and ground monitoring data, the results obtained by the two main algorithms are compared to explore whether the machine learning algorithm has better performance than the empirical method in the TP inversion prediction of Nanyi Lake. The Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) model was used to simulate the TP inflow load in the Nanyi Lake Basin and determine the key pollution source areas. The results show that the accuracy of the machine learning algorithm is higher than that of the empirical method and has better performance. Among the four machine learning algorithms—support vector machines (SVR), artificial neural network (BP), extreme gradient boosting algorithm (XGBoost) and random forest regression (RF)—the TP concentration inversion model established by the XGBoost algorithm is more accurate and has strong spatiotemporal heterogeneity. The simulation results in the southern and northeastern parts of the Nanyi Lake Basin contribute the most to the pollution load of the lake area, and the simulation results can provide direction for the effective prevention and control of Nanyi Lake, help to further effectively identify the key source areas of TP pollution in the water body of Nanyi Lake, and provide a meaningful scientific reference for water quality monitoring and management, to comprehensively improve the water quality of Nanyi Lake.

Evaluating future habitat quality responding to land use change under different city compaction scenarios in Southern China

Rapid urban expansion, accompanied by intense landscape changes, significantly affects natural habitats. Promoting sustainable urban development, such as the compact city strategy, is essential to balance ecosystem conservation and socio-economic development. Previous studies have generally focused on exploring the ecosystem impact of urban expansion concerning the future projections of climate, population, and economic development. Less attention has been paid to how different urban forms modify the landscape and affect habitats at a fine resolution. This study has built a framework to demonstrate future land use change under various city compaction scenarios using a bottom-up Cellular Automata (CA) model and a top-down Markov model. Then the Integrated Valuation of Ecosystem Services and Trade-offs (InVEST) model was incorporated to evaluate the resultant habitat quality. By taking the Guangdong-Hong Kong-Macao Greater Bay Area (GBA) as the study area, three future compact city scenarios in 2040 and 2060 were proposed to examine the accumulative effect of urban growth. The results show that by 2040, the high-compact scenario will cause the highest habitat quality degradation among all scenarios due to marked cropland displacement induced by urban edge expansion. By 2060, intensified medium or low-compact scenarios tend to create new urban clusters outside the existing urban areas, resulting in severe habitat isolation and fragmentation. The GBA presents significant spatial heterogeneity in habitat quality variation because of the uneven development between the core and key node cities. Our results suggest that a collaborative strategy should be promoted to motivate the unique advantages of each city. This could include maintaining the amount and connectivity of open space under city integration processes and reserving high-quality cropland, such as fish-pod-based agriculture, to mitigate habitat quality degradation. This study can provide insights for developing long-term land use management when applying compact city strategies to balance ecological conservation and urban development needs.

Do Ecological Restoration Projects Undermine Economic Performance? A Spatially Explicit Empirical Study in Loess Plateau, China

Exploring the complex relationship between ecological restoration and economic development is valuable for decision makers to formulate policy for sustainable development. The large-scale environmental restoration program—Grain for Green—was mainly implemented in the Loess Plateau of China to improve the soil retention service. However, whether this world-famous program affects local economic development has not been fully explored. In this study, using the Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) model and spatializing the gross domestic product (GDP) based on the remotely sensed nightlight data, we explored the tradeoff between environment (i.e., soil retention service) and economy (i.e., GDP) for the Loess Plateau in a spatially explicit way. We found that the soil retention service increased prominently over the past 40 years, especially after implementing the Grain for Green project. Meanwhile, the GDP increased about nine-fold over the past four decades from 4.52 to 40.29 × 107 USD. A win–win situation of soil retention and economic development was achieved in the Loess Plateau of China, particularly in the loess gully and loess hilly gully regions of the Loess Plateau. The win–win situation of soil retention and economic development was as a result of the Grain for Green program, the optimization of industrial structure, and the increase in non-agriculture employment. Compared with previous studies, more spatial information was available for the Loess Plateau in this study, which is more valuable to policymakers.

Assessment of ecosystem service flow and optimization of spatial pattern of supply and demand matching in Pearl River Delta, China

Exploring the spatial flow pattern of ecosystem services and clarifying the transmission path between the supply area and the demand area will help to formulate more scientific and reasonable ecological protection policies. This paper takes the rapid urbanization area representing the Pearl River Delta urban agglomeration as an example. Using Invest model to quantitative the assessment of the supply and demand of carbon sequestration services and water ecosystem services from 2000 to 2020, a spatial flow model of ecosystem services is constructed to clarify the spatial flow of regional ecosystem services pattern. In addition, the Geo-detector model is used to explore the driving factors of the supply and demand relationship of ecosystem services, and the spatiotemporal geographic weighted regression model is further used to analyze the temporal and spatial differentiation of the impact degree. Finally, based on the Bayesian belief network, the optimal state factor configuration is selected to optimize the spatial pattern, and the corresponding optimization strategy is given. The main conclusions are as follows: (1) The supply of carbon sequestration services in the Pearl River Delta decreased gradually during 2000–2020, while the demand increased gradually. The supply of water ecosystem services increased first and then decreased, while the demand showed a downward trend. (2) In terms of spatial heterogeneity of supply and demand matching, the main driving factors of carbon sequestration services included night light brightness value, temperature and vegetation index; The main driving factors of water ecosystem services include night light brightness value, land use type and vegetation index. (3) In terms of optimal areas for supply and demand matching, carbon sequestration services were mainly distributed in Zhaoqing, Huizhou and Jiangmen; The optimal matching areas of water ecosystem service supply and demand were mainly distributed in Zhaoqing, Guangzhou, Huizhou and other cities.

How can multiscenario flow paths of water supply services be simulated? A supply-flow-demand model of ecosystem services across a typical basin in China

Ecosystems provide many benefits to humans, and among them, water supply is crucial for human survival and development. This research focused on the Yangtze River Basin as the research area, quantitatively evaluated the temporal-spatial dynamic changes in the supply and demand of water supply services and determined the spatial relationship between the supply and demand regions of water supply services. We constructed the supply-flow-demand model of water supply service to quantify its flow. In our research, the Bayesian model was used to establish a multiscenario model of the water supply service flow path to simulate it and clarify its spatial flow path, flow direction and flow magnitude from the supply region to the demand region and determine its changing characteristics and driving factors in the basin. The results show that (1) In 2010, 2015 and 2020, the amount of water supply services showed a decreasing trend and was approximately 133.57 × 1012 m3, 129.97 × 1012 m3 and 120.82 × 1012 m3, respectively. (2) From 2010 to 2020, the trend of the cumulative flow of water supply service flow decreased each year and was 59.814 × 1012 m3, 56.930 × 1012 m3, 56.325 × 1012 m3 respectively. (3) Under the multiscenario simulation, the flow path of the water supply service was generally the same. The proportion of the water supply region was the highest under the green environmental protection scenario, at 73.8 %, and the proportion of the water demand region was the highest under the economic development and social progress scenario, at 27.3 %. (4) The provinces and municipalities in the basin were divided into three types of regions according to the matching relationship between supply and demand: catchment region, flow pass-through region and outflow region. The number of outflow regions was lowest, accounting for 23.53 %% of the regions, while the number of flow pass-through regions was the highest, accounting for 52.94 %.

Regional Water Stress Forecasting: Effects of Climate Change, Socioeconomic Development, and Irrigated Agriculture—A Texas Case Study

Climate change, socioeconomic development, and irrigation management are exacerbating water scarcity in many regions worldwide. However, current global-scale modeling approaches used to evaluate the impact of these factors on water resources are limited by coarse resolution and simplified representation of local socioeconomic and agricultural systems, which hinders their use for regional decision making. Here, we upgraded the irrigation water use simulation in the system dynamics and water environmental model (SyDWEM) and integrated it with the water supply stress index (WaSSI) ecosystem services model. This integrated model (SyDWEM-WaSSI) simulated local socioeconomic and agricultural systems to accurately assess future water stress associated with climate change, socioeconomic development, and agricultural management at subbasin levels. We calibrated the integrated model and applied it to assess future water stress levels in Texas from 2015 to 2050. The water stress index (WSI), defined as the ratio of water withdrawal to availability, was used to indicate different water stress levels. Our results showed that the integrated model captured changes in water demand across various sectors and the impact of climate change on water supply. Projected high water stress areas (WSI > 0.4) are expected to increase significantly by 2050, particularly in the Texas High Plains and Rolling Plains regions, where irrigation water use was projected to rise due to the impact of climate change. Metropolitan areas, including Dallas, Houston, Austin, and San Antonio, were also expected to experience increased domestic water demand, further exacerbating water stress in these areas. Our study highlights the need to incorporate socioeconomic planning into water resources management. The integrated model is a valuable tool for decisionmakers and stakeholders to evaluate the impacts of climate change, socioeconomic development, and irrigation management on water resources at the local scale.

Climatic drought impacts on key ecosystem services of a low mountain region in Germany.

The frequency of extreme weather events has increased in the latest years in Europe. The recent consecutive droughts caused severe damage in many sectors and underlined the demand for adaptation. There is a need for a better understanding of the response of ecosystems to climate change and the consequences for key ecosystem services, such as water supply and carbon sequestration, at a local and regional scale. This paper aims to support decision-making for climate adaptation in a low-mountainous region of central Germany. We analysed the temperature and precipitation trends and drought conditions. The response of two key services (surface water provision and carbon sequestration) to droughts is estimated using an ecosystem service model. The spatially averaged water yield, net ecosystem productivity (NEP), and soil moisture are assessed and compared for the five worst droughts with long-term averages to identify the vulnerable areas and ecosystems. The temperature increased on seasonal and annual scales, while precipitation decreased in some areas in summer and increased in winter and annually. The standardised precipitation-evapotranspiration index (SPEI) showed worsening drought conditions, especially after the late 1980s. Droughts caused a reduction of water yield by 54%, NEP by 18%, and upper zone soil moisture by 13%. The impacts varied spatially, with the central region being worst affected, while the southern part was relatively more resilient. Adaptation is urgently needed to reduce drought risks and enhance climate resilience. Adaptive measures can include amending crop rotations, introducing more drought-tolerant varieties, upgrading agriculture and food industry technology, increasing mixed forests, and reducing non-native tree species.

Spatiotemporal trends in ecosystem carbon stock evolution and quantitative attribution in a karst watershed in southwest China

Karst ecosystems serve as a vital part of the Earth’s ecosystem and have a substantial influence on the worldwide carbon cycle. Revealing the features and driving factors of the spatiotemporal evolution of Carbon (C) stock in karst watersheds is critical for the in-depth exploration of the regional carbon cycle and carbon sources/sinks, as well as in regional ecological restoration. In this study, the Nanming River Basin, a representative karst basin in southwest China, was used as the subject region. Based upon data on land use change from 2000 to 2020, an Integrated Valuation of Ecosystem Services & Tradeoffs (InVEST) model was applied to calculate the C stock from 2000 to 2020 and identify the driving factors of the regional change of C stock using an optimal parameters-based geographical detector (OPGD) model. The findings indicate that: (1) the cumulative reduction of C stock in the basin from 2000 to 2020 was 3.16 × 105 t; the center of gravity of C stock increase has shifted to the southwest by 2434.16 m, and the center of gravity of the reduction has shifted to the southwest by 7260.53 m. (2) The transition of forest land into construction land had the highest contribution to the decrease of C stock (60.91%); the transition of cultivated land and grassland into forest land was conducive to a rise in the C stock, and these conversions contributed 45.93% and 35.00%, respectively, to the increase of C stock. (3) The normalized difference vegetation index (NDVI), population density, intensity of human activity, slope, and lithology all have annual average q-values greater than 10%, meaning they are the primary factors driving the spatial differentiation of C stock. The contribution of the NDVI ∩ slope direction to the regional heterogeneity of C stock was the largest among the interactive driving factors, with an explanatory power close to 30%. The interactive combinations of drivers all showed nonlinear enhancement or two-factor enhancement effects. To some extent, this study deepens the study of changes in C stock and related driving mechanisms in karst areas, intending to provide a scientific foundation for the recovery of fragile ecosystems and to support a regional low-carbon economy.

Ecological function zoning of Nansi Lake Basin in China based on ecosystem service bundles.

Ecological function zoning is an essential means of scientific management of ecosystems. According to the characteristics of ecological function zoning, implementing zoning control is conducive to the governance and protection of the ecological environment and the maintenance of ecological sustainability. This study was conducted with the Nansi Lake Basin as the cross-section for 2018. The Integrated Valuation of Ecosystem Services and Trade-offs model was adopted to assess and measure five ecosystem services, including water yield, crop production, soil conservation, carbon storage and carbon sequestration, and habitat quality. The Self-Organizing Feature Maps neural network was applied to obtain the ecosystem service bundles, and then, the ecological function zones were divided. The results indicated that the overall spatial pattern of ecosystem services in the study zone showed a decreasing schema from east to west; There was a trade-off between supply services and support services and a synergy between supply services and regulatory services; according to the bundling results, the Nansi Lake Basin was divided into four ecological functional zones: the eastern ecological surplus zone, the central crop supply zone, the western ecological balance zone, and the lake habitat protection zone. The results showed that (1) the spatial distribution of various ecosystem services in the Nansi Lake Basin showed spatial heterogeneity and specific regional laws, showing a decreasing pattern from the east to the west as a whole, especially in soil conservation, carbon sequestration, and habitat quality. (2) According to the supply and spatial distribution of each ecosystem service, the Nansi Lake Basin was divided into four ecological functional zones: the eastern ecological surplus zone, the central crop supply zone, the western ecological balance zone, and the lake habitat protection zone. (3) For zone I, provisioning services and regulation services were in synergy. For zone II and zone III, the provisioning service had a trade-off relationship with the regulation service and the supporting service. For zone IV, supporting services were trade-offs not only with provisioning services but also with regulating services. In general, the trade-offs between ecosystem service in the Nansi Lake Basin were stronger than the synergies, and the overall benefits of ecosystem services were smaller. Relying on the perspective of the ecosystem service bundles, at the county level, this study provided an analysis of the trade-offs and synergies among ecosystem services in the Nansi Lake Basin, which helped formulate the management plan for the corresponding region and provided the appropriate recommendations for regional habitat conservation and restoration.

Quantifying the independent contributions of climate and land use change to ecosystem services

Ecosystem services (ESs) are critical to human welfare and play an important role in supporting sustainable social and economic development. Climate change (CLC) and land use change (LUCC) are two of the most important factors influencing ESs. However, few studies have tried to distinguish the independent contributions of CLC and LUCC to ESs. Using meteorological, soil, land use, and remote sensing data for Liaoning Province (China) from 2000 to 2020, the Integrated Valuation of Ecosystem Services and Trade-offs (InVEST) model and Carnegie-Ames Stanford Approach (CASA) model were used to construct scenario simulation frameworks based on three hypothetical scenarios: 1) CLC effect only; 2) LUCC effect only; 3) a combined effect of CLC and LULC. The three scenario simulation frameworks were then used to determine the independent contributions of CLC and LUCC to net primary productivity (NPP), water yield (WY), soil retention (SR), and their temporal dynamics. Results showed that under the combined effect of CLC and LULC, NPP, WY and SR in Liaoning Province exhibited a trend of gradual increase from 2000 to 2020, increasing by 124.62 gC/m2, 30.64 mm/a and 0.63 t/km2, respectively. Under the CLC only scenario, WY and SR changed by 6.24% and 2%, respectively, exhibiting a more significant effect than under the LUCC only scenario. In contrast, NPP changed by 25.71% under the LUCC only scenario, which was more significant than under the CLC only scenario. Overall, CLC was found to be the dominant factor affecting changes in WY and SR in Liaoning Province, with independent contribution rates of 81.79%-84.02% and 73.57%-85.44%, respectively, whereas LUCC was the dominant factor affecting changes in NPP with an independent contribution rate of 86.12%-92.50%. Decreased precipitation levels and an increase in temperature were the two primary factors driving fluctuations in the independent contributions of CLC to WY and SR, while large-scale forest land area damage and rapid urbanization were the two primary factors driving fluctuations in the independent contribution of LUCC to NPP. The results of this study identify the specific effects of different climatic conditions on ESs and highlight the conflict between urbanization and ecosystem service provision, providing a theoretical foundation for improving and increasing ESs and regional sustainable development in Liaoning Province.

Changes in carbon stock in the Xing’an permafrost regions in Northeast China from the late 1980s to 2020

ABSTRACT The degradation of Xing’an permafrost affects the stability of carbon pool and carbon emissions of the hemiboreal ecosystem in Northeast China. Due to the lack of long-term monitoring and detailed research, changes in carbon stock in terrestrial ecosystems in the Xing’an permafrost regions in Northeast China remain little known. In this study, we conducted more accurate simulations for the aboveground biomass (AGB), belowground biomass (BGB), dead organic carbon (DOC), and soil organic carbon (SOC) in the top 0–30 cm in permafrost regions in Northeast China using the Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) model. The model was applied using multi-period land use/land cover (LULC) and carbon density data from the late 1980s, 2000, 2010, and 2020. In Northeast China, the permafrost extent shrank rapidly by 108,600 km2 from 365,300 km2 in the 1980s to 256,700 km2 in the 2010s. The total carbon stock in permafrost regions in Northeast China was estimated at 4293.04 Tg C in the 1980s and at 4049.56 Tg C in the 2010s. Based on the permafrost extent of the 1980s, it was estimated that from the late 1980s to 2020, the LULC transformation resulted in the reduction of carbon stock by 33.53 Tg C, while the carbon fixation of vegetation growth increased by 1205.18 Tg C, i.e. a net carbon accumulation of 1149.15 Tg C. However, this estimate of the increasing carbon pool still awaits more systematic studies on the carbon budgets at larger soil depths of the top 2–3 m soils. This estimate can provide a timely preliminary estimate of the carbon pool as the baseline in the permafrost region of Northeast China for national and regional initiatives of carbon neutralization.

Informing watershed management in data-scarce Indian Himalayas

Anthropogenic water stress, especially in mountain habitats worldwide, affects water supply and threatens water security. Evaluating past trends, assessing current conditions, and anticipating future change is paramount for the sustainable use of increasingly scarce freshwater resources. This study simulates water yield using the Integrated Valuation of Ecosystem Services and Trade-offs (InVEST) model to generate reliable information for decision-making related to watershed management programs in data-scarce Himalayan regions. The results are translated into watershed indices easily communicable to watershed managers, stakeholders and administrative agencies. The analysis demonstrates the utility of hydrological modeling using limited data within a scoping protocol for the pre-implementation phase of any watershed management program.

Spatio-temporal evolution and prediction of carbon storage in Kunming based on PLUS and InVEST models.

Carbon storage is a critical ecosystem service provided by terrestrial environmental systems that can effectively reduce regional carbon emissions and is critical for achieving carbon neutrality and carbon peak. We conducted a study in Kunming and analyzed the land utilization data for 2000, 2010, and 2020. We assessed the features of land utilization conversion and forecasted land utilization under three development patterns in 2030 on the basis of the Patch-generating Land Use Simulation (PLUS) model. We used the Integrated Valuation of Ecosystem Services and Trade-offs (InVEST) model to estimate changes in carbon storage trends under three development scenarios in 2000, 2010, 2020, and 2030 and the impact of socioeconomic and natural factors on carbon storage. The results of the study indicated that (1) carbon storage is intimately associated with land utilization practices. Carbon storage in Kunming in 2000, 2010, and 2020 was 1.146 × 108 t, 1.139 × 108 t, and 1.120 × 108 t, respectively. During the 20 years, forest land decreased by 142.28 km2, and the decrease in forest land area caused a loss of carbon storage. (2) Carbon storage in 2030 was predicted to be 1.102 × 108 t, 1.136 × 108 t, and 1.105 × 108 t, respectively, under the trend continuation scenario, eco-friendly scenario, and comprehensive development scenario, indicating that implementing ecological protection and cultivated land protection measures can facilitate regional ecosystem carbon storage restoration. (3) Impervious surfaces and vegetation have the greatest influence on carbon storage for the study area. A spatial global and local negative correlation was found between impervious surface coverage and ecosystem carbon storage. A spatial global and local positive correlation was found between NDVI and ecosystem carbon storage. Therefore, ecological and farmland protection policies need to be strengthened, the expansion of impervious surfaces should be strictly controlled, and vegetation coverage should be improved.

Integrating forest cover change and carbon storage dynamics: Leveraging Google Earth Engine and InVEST model to inform conservation in hilly regions

Forests are vital in combating climate change by storing and sequestrating CO2 from the atmosphere. Measuring the influence of land use/land cover (LULC) changes on the capacity of carbon storage (CS) within forest ecosystems presents a significant challenge. This study employs remote sensing techniques to examine the changes in spatiotemporal patterns of CS in the Chittagong Hill Tracts (CHT), resulting from LULC alterations between 1996 and 2021. LULC change patterns were identified for six different years utilizing the Google Earth Engine (GEE). The Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) model was combined with GEE to evaluate the changing patterns of CS. The study discovered that the CHT region experienced a loss of 21.65 × 106 Mg of CS, owing to a 21% reduction in vegetation cover (2862.85 km^2) during the study period. The central city area (Chittagong) accounted for the most significant loss of CS (7.99 × 106 Mg), while the suburban areas of Khagrachari (0.92 × 106 Mg) and Rangamati (3.53 × 106 Mg) contributed the least. The multiple regression model revealed that elevation and vegetation characteristics significantly influenced CS. The findings underscore the importance of developing policies and strategies that mitigate the adverse effects of land cover change on CS, and advocate for sustainable forest management practices that strike a balance between ecological, social, and economic concerns.

Increase of carbon storage in the Qinghai-Tibet Plateau: Perspective from land-use change under global warming

Under climate change, land use has an essential effect on the carbon cycle in the climate change sensitive area of Qinghai-Tibet Plateau (QTP). This study about ambitions to check out the spatial and temporal patterns of carbon storage (CS) on the QTP under future land-use changes and their influencing factors. Based on historical and projected climate and land-use information and the compiled carbon-intensity dataset derived from 839 sampling points, we projected future changes in CS in the region. We projected changes of CS in the QTP in the near-term (2021–2040), mid-term (2041–2060), and long-term (2081–2100) periods, using the Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) model. We found that the total carbon storage (TCS) from 1980 to 2020 was approximately equal to 247–259 × 108 t, where Csoil had the greatest contribution (about 88% of the TCS), while Cabove, Cbelow and Cdead accounted for approximately 5%, 5% and 2% of the TCS, respectively. Furthermore, the TCS decreased from southeast to northwest, corresponding to decreasing forest coverage and increasing unused land area in the QTP. Compared to the baseline period (1995–2014, 259 × 108 t), the CS in the QTP under the Shared Socioeconomic Pathways (SSPs) is expected to increase by 7.3–13.5%, 6.2–14.7% and 5.4–14.3% in the three future periods, respectively. Spatially, the carbon increase will be concentrated in the southeastern and northern parts of the QTP, where the land-use types are mainly forest land and grassland. Increases in precipitation and temperature are predicted to take place for the duration of the QTP in the future, driving land-use changes that are projected to result in increased area of forest land, which would increase CS. The CS in QTP is high, being influenced by land use and climatic factors, and future climate change may enhance the carbon sink capacity of the QTP.

Coupling and Coordination Relationship between Urbanization Quality and Ecosystem Services in the Upper Yellow River: A Case Study of the Lanzhou–Xining Urban Agglomeration, China

The study of the man–land relationship in the urbanization process is the current frontier and focus of international research. How to balance urban development and ecosystem conservation in the Upper Yellow River is a key issue for sustainable development in China. In this study, we evaluated the Lanzhou–Xining urban agglomeration (LXUA) by constructing a multi-dimensional assessment system for urbanization quality and ecosystem services. The efficacy function model, entropy weight method, and Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) model were used to quantitatively assess the subsystems’ state of development. Then, the coupling model (CD) and the coordination degree (CCD) model were used to explore the coupling coordination relationship and spatial-temporal change characteristics of the composite system. The findings indicate that: (1) In 2020, the quality of urbanization in the LXUA showed the pattern of “double core”. The development of urban centers in each city is insufficient, and the proportion of counties with a low level is too high. (2) Integrated ecosystem services showed an increasing distribution pattern from the northeast to the southwest. Water provision services, soil conservation services and carbon fixation services all showed growth trends. (3) Each county’s composite system was in the run-in stage or highly coupled stage. The subsystems were closely related to each other. (4) The CCD was decreased by 6% between two decades. The number of counties on the verge of disorder was the highest. About 80% of the counties were relatively lagging behind in ecosystem services.

The supply and demand of water-related ecosystem services in the Asian water tower and its downstream area

Climate change and human activities can have an impact on the supply and demand of water-related ecosystem services (WRESs) in the Asian water tower (AWT) and its downstream area, which is closely related to the production and livelihoods of billions of people. However, few studies have taken the AWT and its downstream area as a whole to assess the supply–demand relationship of WRESs. This study aims to assess the future trends of the supply–demand relationship of WRESs in the AWT and its downstream area. Here, the supply–demand relationship of WRESs in 2019 was assessed using the Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) model and socio-economic data. Then, future scenarios were selected under the framework of the Scenario Model Intercomparison Project (ScenarioMIP). Finally, trends in the supply–demand of WRESs were analysed at multiple scales from 2020 to 2050. The study found that the supply–demand imbalance of WRESs in the AWT and its downstream area will continue to intensify. The area with imbalance intensification was 2.38 × 106 km2 (61.7 %). The supply–demand ratio of WRESs will decline significantly under different scenarios (p < 0.05). The main reason for the imbalance intensification in WRESs is the constant growth of human activities, with a relative contribution of 62.8 %. Our findings suggest that in addition to the pursuit of climate mitigation and adaptation, attention should also be paid to the impact of rapid human activity growth on the supply–demand imbalance of WRESs.