Integrated Valuation Of Ecosystem Services And Tradeoffs Research Articles

Spatiotemporal simulation of sustainable development based on ecosystem services under climate change.

This study explores the spatiotemporal distribution characteristics of ecosystem services (ESs) in the karst region of southeastern Yunnan under the backdrop of climate change. The study innovatively calculates the sustainable development goals (SDG) index based on ecosystem services (ESs). It employs the patch-generating land use simulation (PLUS) model to simulate future land use changes (LUCs) and uses the integrated valuation of ecosystem services and tradeoffs (InVEST) model to assess ESs under different scenarios. This research systematically evaluates the ESs and SDGs in karst regions within the context of climate change. The results indicate that: (1) Under all three scenarios in 2035, the trend of LUCs in the karst area of southeastern Yunnan is highly consistent, though the intensity and spatial configuration vary significantly. The least reduction in arable land area occurs under the shared socioeconomic pathways (SSP) 126 scenario, while water bodies and construction land show varying degrees of increase; (2) Regarding ESs, both water yield and soil retention exhibit an increasing trend across all scenarios by 2035, with the most notable rise under SSP126. Conversely, habitat quality and carbon storage show a decline, with the smallest decrease also under SSP126; (3) Analyzing the SDG index, the overall value is low in 2020. In future scenarios, the SDG index increases in the southern part while decreasing in the eastern part, indicating significant differences in regional sustainable development potential. Hotspots under SSP126 and SSP245 are concentrated in the densely vegetated southwest and eastern edge areas, while cold spots are mainly found in the heavily human-impacted central Yunnan urban agglomeration and Wenshan City. This study systematically explores for the first time the spatiotemporal dynamics of ESs in the karst region of southeastern Yunnan under different climate scenarios. It provides scientific evidence for regional ecological protection and land use planning.

Spatiotemporal characteristics of human activity and land use on ecosystem service functions in mountainous areas of Northeast Guizhou, Southwest China

With the rapid advancement of urbanization and industrialization, intense land utilization in mountainous areas has led to ecological and environmental issues, and also causing a gradual degradation of ecosystem services. Investigating the spatiotemporal characteristics of human activities on land use and ecosystem services in mountainous areas holds significant practical importance for local ecological conservation and land management. This study utilizes human activity and land use models to evaluate the complex relationship between humans and land in the northeastern Guizhou, employs the Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) and the Modified Universal Soil Loss Equation (RUSLE) models to conduct an in-depth investigation into the spatiotemporal distribution of soil conservation (SC), water yield (WY), carbon sequestration (CS), habitat quality (HQ), and landscape aesthetics (LA). Besides, we utilized the Pearson correlation coefficient and spatial bivariate models to scrutinize the spatial heterogeneity and interactions among these ecosystem services. The results revealed a significant escalation in the intensity of human activity and land use within the study area, with values rising from 0.483 and 316 in 2000 to 0.695 and 351 in 2020, respectively. For 2000–2020, the added value of SC and WY experienced a change of 1.179 t‧hm−2 and 118.503 mm, respectively, while the CS, HQ, and LA have largely remained stable. The spatial distribution of ecosystem service functions exhibited distinct patterns of trade-offs and synergies. The ecosystem's multifunctional benefits were predominantly concentrated in the northern sector of the study area, with the maximum migration distance of class IV hotspots recorded at 70.431 km. Over time, the impact of human activities and land use on ecosystem services has been escalating. Studying the interactions between human activities and land use and their impact on ecosystem services can help us develop land use policies and ecological management strategies.

Spatiotemporal Assessment of Habitat Quality in Sicily, Italy

We measured the spatiotemporal dynamics of habitat quality (HQ) in Sicily in two different reference years, 2018 and 2050, assuming a business-as-usual scenario. To estimate HQ and related vulnerability, we used the Integrated Valuation of Ecosystem Services and Trade-offs (InVEST) Habitat Quality model and data on land use/land cover provided by the Esri Land Cover 2050 project. We also implemented a Coarse–Filter approach to validate the reliability of HQ measures and detect biodiversity hotspots that require priority conservation. Further, we used spatial statistic tools for identifying clusters or hotspot/coldspot areas and uncovering spatial autocorrelation in HQ values. Finally, we implemented a geographically weighted regression (GWR) model for explaining local variations in the effects on HQ estimates. The findings reveal that HQ in Sicily varies across space and time. The highest HQ values occur in protected areas and forests. In 2018, the average HQ value was higher than it was in 2050. On average, HQ decreased from 0.29 in 2018 to 0.25 in 2050. This slight decline was mainly due to an increase in crop and urbanized areas at the expense of forests, grasslands, and bare lands. We found the existence of a positive spatial autocorrelation in HQ, demonstrating that areas with higher or lower HQ tend to be clustered, and that clusters come into contact randomly more often in 2050 than in 2018, as the overall spatial autocorrelation moved from 0.28 in 2018 to 1.30 in 2050. The estimated GWR model revealed the sign and the significance effect of population density, compass exposure, average temperature, and patch richness on HQ at a local level, and that such effects vary either in space and time or in significance level. Across all variables, the spatial extent of significant effects intensifies, signaling stronger localized influences in 2050. The overall findings of the study provide useful insights for making informed decisions about conservation and land planning and management in Sicily.

Integrated Evaluation of the Ecological Security Pattern in Central Beijing Using InVEST, MSPA, and Multifactor Indices

Scientific identification of ecological sources and corridors is crucial in constructing an ecological security pattern (ESP). To develop an ESP tailored to the scale of central urban areas in megacities, this study takes Central Beijing as the research object. It innovatively integrates the integrated valuation of ecosystem services and tradeoffs (InVEST), the morphological spatial pattern analysis (MSPA), and the Conefor software to identify ecological sources. Seven indicators related to topographic, natural conditions, and human disturbance factors are selected to build the ecological resistance surface, which is then combined with circuit theory to construct the ESP. The results show the following: (1) Central Beijing contains 157 ecological sources, primarily distributed in the western, northern, and eastern regions, with woodland as the dominant land type. (2) A total of 439 ecological corridors were extracted, including 317 key ecological corridors and 122 inactive ecological corridors. (3) The identified ecological pinch points are mainly the Jingmi Diversion Canal and the West Moat. (4) The identified ecological barriers are spread throughout the entire study area. The results of this study are highly significant for improving the quality of ecological security and protecting biodiversity in the study area and other urban centers.

Ecological risk assessment and response prediction caused by LUCC in the central Yunnan Province

With the acceleration of urbanization, unreasonable land use poses a serious threat to ecological security. However, there is still some space for improvement in the existing assessment of ecological risks (ERs) caused by land use/land cover change (LUCC). Therefore, this study takes the central Yunnan Province (CYP) as an example, and uses the Patch-Generating Land Use Simulation (PLUS) model and the Integrated Valuation of Ecosystem Services and Trade-offs (InVEST) model to simulate the land use/land cover (LULC) in different scenarios in the future, calculate the ecosystem services (ESs) from 2000 to 2020 and the next 20 years, as well as ERs of various types of ESs caused by LUCC. In addition, the Pearson correlation coefficient and geographically weighted regression (GWR) are used to analyze the trade-off and synergy relationships between various ecological risks, and the geographic detector method (GDM) is used to analyze their driving factors. The research results indicate that: (1) there have been significant changes in LULC in the CYP in the past 20 years. (2) There was significant spatial heterogeneity among various types of ESs in the CYP. (3) In the past 20 years, the distribution range of ERs has been relatively large, with significant spatial differences. (4) The ERs caused by LUCC in the next 20 years generally show a decreasing trend, and the ecological high-risk areas are mainly concentrated on construction land. (5) The ERs associated with ecosystem service types are mainly synergistic. ER is influenced by a combination of natural factors, socio-economic factors, and distance factors, with some factors having strong interactions. In short, the future ERs of CYP have decreased, and the ERs corresponding to various ecosystem services (ESs) interact with each other, causing a ripple effect. Finally, this study proposes policy recommendations to alleviate ERs in the CYP.

Optimizing nature-based solutions for urban flood risk mitigation: A multi-objective genetic algorithm approach in Gdańsk, Poland.

Nature-based Solutions (NbS) have emerged as a sustainable approach to managing flood risks by enhancing natural water retention and reducing surface runoff in urban areas. As climate change and rapid urbanization exacerbate flood hazards, optimizing the spatial deployment of NbS is crucial for improving urban resilience and mitigating flood impacts. This study presents a comprehensive optimization framework for the spatial allocation of fourteen different NbS types aimed at mitigating urban flood risks in Gdańsk, Poland. Leveraging a genetic algorithm alongside the Urban Flood Risk Mitigation (UFRM) model of the Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) software suite, we identified areas of the city most vulnerable to pluvial flooding and optimized NbS placement to maximize water retention and reduce runoff. The optimization process balanced multiple objectives, including minimizing implementation costs and maximizing water retention capacity, ensuring that the solutions are both economically feasible and environmentally effective. Three distinct scenarios were proposed: a cost-effective solution, a high-retention solution, and a balanced solution, offering urban planners a range of strategies to address flood risks based on their specific priorities and constraints. Results demonstrated considerable variations in water retention effectiveness across different NbS configurations, with denser urban regions showing the most significant improvements from targeted interventions. The optimized placement of NbS resulted in estimated total water retention improvement of approximately 15.5% for the best solution considered. These findings provide valuable insights for integrating NbS into urban flood management strategies, enhancing citywide resilience, sustainability, and long-term flood mitigation.

Sub-District Level Spatiotemporal Changes of Carbon Storage and Driving Factor Analysis: A Case Study in Beijing

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.

Carbon Storage Response to Land Use/Land Cover Changes and SSP-RCP Scenarios Simulation: A Case Study in Yunnan Province, China.

Changes in terrestrial ecosystem carbon storage (CS) affect the global carbon cycle, thereby influencing global climate change. Land use/land cover (LULC) shifts are key drivers of CS changes, making it crucial to predict their impact on CS for low-carbon development. Most studies model future LULC by adjusting change proportions, leading to overly subjective simulations. We integrated the Integrated Valuation of Ecosystem Services and Trade-offs (InVEST) model, the Patch-generating Land Use Simulation (PLUS) model, and the Land Use Harmonization 2 (LUH2) dataset to simulate future LULC in Yunnan under different SSP-RCP scenarios of climate and economic development. Within the new PLUS-InVEST-LUH2 framework, we systematically analyzed LULC alterations and their effects on CS from 1980 to 2040. Results demonstrated that: (1) Forestland had the highest CS, whereas built-up land and water showed minimal levels. Western areas boast higher CS, while the east has lower. From 1980 to 2020, CS continuously decreased by 29.55 Tg. In the wake of population increase and economic advancement, the area of built-up land expanded by 2.75 times. Built-up land encroaches on other land categories and is a key cause of the reduction in CS. (2) From 2020 to 2040, mainly due to an increase in forestland, CS rose to 3934.65 Tg under the SSP1-2.6 scenario, whereas under the SSP2-4.5 scenario, primarily due to a reduction in forestland and grassland areas, CS declined to 3800.86 Tg. (3) Forestland is the primary contributor to CS, whereas the ongoing enlargement of built-up land is causing a sustained decline in CS. Scenario simulations indicate that future LULC changes under different scenarios will have a significant impact on CS in Yunnan. Under a green sustainable development pathway, Yunnan can exhibit significant carbon sink potential. Overall, this research offers a scientific reference for optimizing land management and sustainable development in Yunnan, aiding China's "double carbon" goals.

Integrating river transport processes and seasonal dynamics to assess watershed nitrogen export risk.

Excessive nitrogen exported to water bodies affects the balance of ecosystem and poses a threat to human health. Although the concept of water purification service helps quantify nitrogen export, the impact of river transport remains unclear. This study focused on nitrogen as a pollutant by utilizing the Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) model to assess nitrogen export in the Dongting Lake Basin, taking into account both the processes of sub-basin nitrogen export and river transport. Additionally, the monthly variations within the year were further explored, together with the identification of the priority area of returning cropland to forest land. The results showed that in 2021, the total nitrogen load outside the Dongting Lake was 11.34×108 kg·year-1, with the sub-basins retaining a total of 9.02×108 kg·year-1, accounting for 79.57% of the total nitrogen load. Notably, the total nitrogen retention by the river made up 16.87% of the total nitrogen retention, up to 1.83×108 kg·year-1. In view of monthly variation, water purification service based on the entire process was higher in winter and late autumn, and lower in summer and early autumn. The priority areas for ecological project were mainly distributed around the Dongting Lake, achieving an improvement of 58.15% in water purification service with approximately 7.02% of the total returnable cropland. This study proposed a new approach of water purification service assessment through integrating river transport processes and seasonal dynamics, aiming to assess watershed nitrogen export risk more accurately.

Spatial–Temporal Variation and Driving Forces of Carbon Storage at the County Scale in China Based on a Gray Multi-Objective Optimization–Patch-Level Land Use Simulation–Integrated Valuation of Ecosystem Services and Tradeoffs–Optimal Parameter-Based Geographical Detector Model: Taking the Daiyun Mountain’s Rim as an Example

Exploring and predicting the spatiotemporal evolution characteristics and driving forces of carbon storage in typical mountain forest ecosystems under land-use changes is crucial for curbing the effects of climate change and fostering sustainable, eco-friendly growth. The existing literature provides important references for our related studies but further expansion and improvements are needed in some aspects. This study first proposed an integrated framework comprising gray multi-objective optimization (GMOP), Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST), the Patch-level Land Use Simulation Model (PLUS), and optimal parameter-based geographical detector (OPGD) models to further expand and improve on existing research. Then, the integrated model was used to analyze the spatial–temporal variation in land-use pattern and carbon storage at the county scale in China’s Daiyun Mountain’s Rim under four scenarios in 2032, and analyze the driving force of spatial differentiation of carbon storage. The results indicated that (1) land-use change primarily involves the mutual transfer among forest, cultivated, and construction land, with approximately 7.2% of the land-use type area undergoing a transition; (2) in 2032, the natural development scenario projects a significant reduction in forest land and an expansion of cultivated, shrub, and construction lands. Conversely, the economic priority, ecological priority, and economic–ecological coordinated scenarios all anticipate a decline in cultivated land area; (3) in 2032, the natural development scenario will see a 2.8 Tg drop in carbon stock compared to 2022. In contrast, the economic priority, ecological priority, and economic–ecological coordinated scenarios are expected to increase carbon storage by 0.29 Tg, 2.62 Tg, and 1.65 Tg, respectively; (4) the spatial differentiation of carbon storage is jointly influenced by various factors, with the annual mean temperature, night light index, elevation, slope, and population density being the key influencing factors. In addition, the influence of natural factors on carbon storage is diminishing, whereas the impact of socioeconomic factors is on the rise. This study deepened, to a certain extent, the research on spatiotemporal dynamics simulation of carbon storage and its driving mechanisms under land-use changes in mountainous forest ecosystems. The results can serve to provide scientific support for carbon balance management and climate adaptation strategies at the county scale while also offering case studies that can inform similar regions around the world. However, several limitations remain, as follows: the singularity of carbon density data, and the research scope being confined to small-scale mountainous forest ecosystems. Future studies could consider collecting continuous annual soil carbon density data and employing land-use simulation models (such as PLUS or CLUMondo) appropriate to the study area’s dimensions.

Spatiotemporal Changes in Ecological Network Structure and Enhancing Territorial Space Management in Guilin, China

Accelerated urbanization and the excessive exploitation of the tourism industry are leading to a diminution of ecological spaces in tourist cities. Ecological networks are an effective method for improving patch connectivity and maximizing ecological space. However, previous research on ecological networks predominantly focuses on static snapshots, ignoring the fact that ecological networks are landscape entities with considerable spatiotemporal and structural dynamics changes. To fill this gap, we first constructed ecological networks of Guilin in 1990, 2000, 2010, and 2020, employing the integrated valuation of ecosystem services and tradeoffs (InVEST) model, the morphological spatial pattern analysis (MSPA) method, and circuit theory. Subsequently, we analyzed the spatiotemporal evolution of the ecological networks and proposed strategies for improving territorial space management. The results showed that ecological sources and corridors were generally decreasing in both number and areas (length), coupled with a notable increase in the number of ecological pinch points and barriers over the 30-year period. The spatiotemporal dynamics of ecological corridors, pinch points, and barriers were associated with ecological sources. Structural evaluation of the ecological networks revealed that during 1990~2020, the value of α (network closure) exceeded 0.7, the value of β (line point rate) surpassed 2, and the value of γ (network connectivity) was greater than 0.8, indicating robust overall connectivity within the ecological networks. The observed decline in these three indicators over time suggested a reduction in connectivity and the available dispersal pathways for species within the ecological networks, highlighting the need for protective measures and optimization strategies. Consequently, the ecological network conservation strategies and the development of ecological patterns were proposed to enhance ecological space management in Guilin. This study addresses a critical knowledge gap in the dynamics of ecological networks and offers valuable insights for mitigating habitat fragmentation and enhancing ecological space management of tourist cities.

Assessment of dynamic water yield using multi scenario of LULC in Cisadane Watershed West Java, Indonesia

Uncontrolled economic development often leads to land degradation, a decline in ecosystem services, and negative impacts on community welfare. This study employs water yield (WY) modeling as a method for environmental management, aiming to provide a comprehensive understanding of the relationship between Land Use Land Cover (LULC), Land Use Intensity (LUI), and WY to support sustainable natural resource management in the Cisadane Watershed, Indonesia. The objectives include: (1) analyzing changes in WY for 2010, 2015, and 2021; (2) predicting WY for 2030 and 2050 under two scenarios—Business as Usual (BAU) and Protected Forest Area (PFA); (3) assessing the impacts of LULC and climate change on WY; and (4) exploring the relationship between LUI and WY. The Integrated Valuation of Ecosystem Services and Trade-offs (InVEST) model calculates actual and predicted WY conditions, while the Coupling Coordination Degree (CCD) analyzes the LULC-WY relationship. Results indicate that the annual WY in 2021 was 215.8 × 108 m³, reflecting a 30.42% increase from 2010. Predictions show an increasing trend in WY under both scenarios for 2030 and 2050 with different magnitudes. Rainfall contributes 88.99% more dominantly to WY than LULC. Additionally, around 50% of districts exhibited unbalanced coordination between LUI and WY in 2010 and 2020. This study reveals the importance of ESs in sustainable watershed management amidst increasing demand for natural resources due to population growth.

Study on the Spatiotemporal Evolution of Habitat Quality in Highly Urbanized Areas Based on Bayesian Networks: A Case Study from Shenzhen, China

Rapid urbanization presents significant challenges to biodiversity through habitat degradation, fragmentation, and loss. This study focuses on Shenzhen, China, a highly urbanized region experiencing substantial land use changes and facing a considerable risk of biodiversity decline, to investigate the dynamics of habitat quality over two critical periods: 2010–2015 and 2015–2020. Using the InVEST (Integrated Valuation of Ecosystem Services and Trade-offs) model for habitat quality assessment and Bayesian networks to analyze causal relationships, this research offers an innovative comparison between habitat recovery and degradation across these two phases. Results indicate that from 2010 to 2015, localized habitat recovery was achieved on 0.53% of the land area due to restoration policies, yet the overall trend remained negative. During the 2015–2020 period, habitat degradation intensified (7.19%) compared to recovery (5.7%); notably, 70.6% of areas that had been previously restored are now experiencing degradation once again. This re-degradation highlights the instability of earlier restoration efforts under ongoing urban pressure. By integrating spatial analysis with Bayesian network modeling, this study provides offers a nuanced understanding of where and why initial recovery efforts were unsuccessful, identifying areas susceptible to persistent degradation. The research emphasizes that urban expansion—particularly the development of construction land, was the primary driver of habitat degradation, while ecological sensitivity played a crucial role in determining the long-term success of recovery efforts. This approach provides valuable insights for designing more effective, sustainable conservation strategies in rapidly urbanizing regions.

Study on the Impact of Spatiotemporal Changes in the Ecological Environment on Grain Crops in the Subtropical Monsoon Climate Zone

Global warming and land-use type shifting lead to the degradation of natural habitats. The research on the ecological and environmental impact of the subtropical monsoon climate zone on food crop cultivation is not systematic enough. An Integrated Valuation of Ecosystem Services and Trade-offs (InVEST)–Patch-generating Land Use Simulation (PLUS)–Maximum Entropy (MaxEnt) model was created to provide a comprehensive assessment of the spatiotemporal variations for food crop habitat quality (HQ) in China’s subtropical monsoon climate zone from 2010 to 2030. The HQ degradation trend was obvious during 2010–2030 under the influence of land-use change. The expansion of lower habitat areas was larger than that of medium and higher habitat areas. The shared socio-economic pathways SSP-CP and SSP-EP increased the mean total area of suitable areas compared with the SSP-ND scenario for food crops by 9% and 17.8%, respectively. Land-use shifts increased the suitable range of food crops and mitigated the negative impacts of urban expansion on food growth. This research has theoretical guidance for land-use planning for food crop production in subtropical monsoon climate zones.

Assessing the Interaction Impacts of Multi-Scenario Land Use and Landscape Pattern on Water Ecosystem Services in the Greater Bay Area by Multi-Model Coupling

Water ecosystem services (WESs) are intrinsically associated with the livelihood of urban residents and are frequently disrupted by human activities. Land use and landscape patterns are key driving factors of alterations in WESs. However, existing research primarily quantifies single-factor influences and often overlooks the interactions between these factors. This study addresses this gap by employing a multi-model coupling approach, integrating the Patch-generating Land Use Simulation (PLUS), Integrated Valuation of Ecosystem Services and Trade-offs (InVEST) model, and Geographical Detector (GD) models alongside various indicators to analyse the evolution of land use, landscape patterns and WESs in the Greater Bay Area from 2000 to 2020, and to simulate spatio-temporal change patterns in different scenarios from 2030 to 2050. Additionally, this study examines the multi-factorial interactions between land use, landscape patterns, and WESs. The results indicate that (1) urbanisation steadily increased, leading to intensified landscape fragmentation, and water yield (WY) and total phosphorus (TP) consistently increased, while total nitrogen (TN) in water gradually decreased; (2) urban areas exerted the most significant impact on WY in the Greater Bay Area while Patch density (PD) had a stronger influence on WY, and Shannon’s diversity index (SHDI) had the most pronounced effect on TN and TP; (3) the interaction between any two land-use types or landscape indices exerted a greater impact on WESs compared with the impact of individual factors alone. The interaction between urban areas and cropland substantially influenced WY (q¯ = 0.634) and most strongly affected TN and TP in water (q¯ = 0.74 and 0.73, respectively). SHDI and PD had the most significant impact on WY in the economic development scenario (q¯ = 0.19) and exhibited the greatest influence on the TN and TP levels in the ecological priority scenario (q¯ = 0.12 and 0.15, respectively). Our findings can provide theoretical and technical support for the integrated scientific planning of regional water ecosystems and the development of comprehensive land use policies in the future.

Significant negative impact of human activities on carbon storage in the Yellow River Delta over the past three decades

With the increasing intensification of human activities, significant changes in land use and land cover (LULC) have posed a severe threat to the carbon storage capacity of wetland ecosystems. A deep understanding of this impact is crucial for protecting regional ecosystems and promoting sustainable development. This study utilized the Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) model and the human activity intensity (HAI) index to conduct detailed grid analysis and global analysis of carbon storage through creating fishnet system and explored the complex relationship between carbon storage and HAI in the Yellow River Delta (YRD), China. The results indicated that over the past 30 years, natural wetlands such as meadow wetlands and salt marshes in the study area had undergone significant degradation due to escalating human activities, while artificial wetlands and non-wetland areas expanded. Concurrently, the total regional carbon storage had declined by 2.08 Tg, representing a significant drop of 8.22 % in the YRD from 1990 to 2020. Among them, dry land, as the primary land type, served as the most crucial carbon pool. Additionally, the human activity intensity of land surface (HAILS) increased significantly, with a growth rate of 37.27 %. HAI mapping revealed a continuous expansion of areas with high HAI. In contrast, the Yellow River Delta National Nature Reserve (YRDNNR) maintained relatively low HAI. Correlation analysis further showed the significant negative correlation (p < 0.01) between carbon storage and HAI, with r values of grid analysis ranging from −0.1395 to −0.0334, while that for global analysis was −0.9643, respectively. This reflected the spatial heterogeneity and agglomeration effects of data analysis across different scales. This study provides valuable insights for achieving the “dual carbon” goals and supporting the conservation and management of wetland ecosystems.

Integrated spatial prioritization of urban nature-based solutions for climate adaptation, mitigation, and justice

ABSTRACT In densely populated cities, people confront multiple impacts of climate change, including stormwater runoff, flooding, heat waves, and health issues. To address these impacts, nature-based solutions (NbS) have gained significant attention in recent years due to their potential to contribute to sustainability, resilience, and ecosystem services. Nevertheless, more research is required to understand the wider potential of NbS and to identify priority areas for their deployment. This study developed an analytical approach and implemented it in the Tehran Metropolitan Area (TMA) by considering factors related to NbS co-benefits. The approach included spatial prioritization, spatial correlation analysis, and suitability analysis. It combines a Geographic Information System, Integrated Valuation of Ecosystem Services and Trade-offs (InVEST) model, Zonation, Best-Worst Method, Bivariate Local Indicator of Spatial Autocorrelation analysis (BiLISA), a Fuzzy Inference System, and Boolean overlay analysis. The results include maps showing priority areas for different types of NbS and spatial co-benefits and mismatches. High-priority areas are located in disadvantaged areas. In total, 105.73 km2 (17% of the TMA) was designated as highly prioritized. We show that various NbS interventions are applicable, with green roofs and rainwater harvesting being the most feasible. This study can assist decision-makers in optimizing NbS to deliver maximum co-benefits.

Land use modeling and carbon storage projections of the Bosten Lake Basin in China from 1990 to 2050 across multiple scenarios

Given the escalating issue of global climate change, it is imperative to comprehend and quantify the effects of land use change on carbon storage (CS), which pertains not only to the preservation of ecosystem functions but also directly influences the equilibrium and stability of the global carbon cycle. This study examines the correlation between CS and land use change, forecasts the future spatial distribution of CS, and offers a reference for the rational planning of watershed space. Focusing on the Bosten Lake Basin of Xinjiang in China, employing the land use simulation (PLUS) model and the integrated valuation of ecosystem services and trade-offs (InVEST) model to forecast the spatial distribution of carbon stocks across three developmental scenarios, while also examining the shift in the center of gravity of CS and the autocorrelation of their spatial distribution. The findings derived from the study are as follows: (1) From 1990 to 2020, the predominant land use type in the Bosten Lake Basin was grassland, while there was an upward trend in the areas of cropland, forest land, built-up land, and wetland, alongside a downward trend in the areas of grassland, water, and unused land. (2) In the long term, the regional CS exhibits an upward trend, with the most significant increase anticipated in the EPS scenario. Grassland constitutes the most extensive carbon reservoir in the Bosten Lake Basin, while wetlands exhibit the highest carbon sequestration potential. (3) The alteration in the center of gravity of CS is associated with the expansion or reduction of the major regional carbon reservoirs and types characterized by significant carbon sequestration potential. (4) In the long term, the spatial correlation of CS in the Bosten Lake Basin exhibits a consistent upward trend, with the most pronounced spatial correlation observed under EPS.

Quantifying the Effect of Land Use and Land Cover Changes on Spatial-Temporal Dynamics of Water in Hanjiang River Basin

As a vital part of the geo-environment and water cycle, ecosystem health and human development are dependent on water resources. Water supply and demand are influenced significantly by land use and cover change (LUCC) which shapes the surface ecosystems by altering their structure and function. Under future climate change scenarios, LUCC may greatly impact regional water balance, yet the impact is still not well understood. Therefore, examining the spatial relationship between LUCC and water yield services is crucial for optimizing land resources and informing sustainable development policies. In this study, we focused on the Hanjiang River Basin and used the patch-generating land use simulation (PLUS) model, coupled with the Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) model, to assess water yield services under three Shared Socioeconomic Pathway and Representative Concentration Pathway (SSP-RCP) scenarios. For the first time, we considered the impact of future changes in socio-economic and water use indicators on water demand using correction factors and ARIMA projections. The relationship between water supply and demand was explored using this approach, and LUCC’s effects on this balance are also discussed. Results indicate that: (1) The patterns of LUCC are similar for the three scenarios from 2030 to 2050, with varying levels of decrease for cropland and significant growth of built-up areas, with increases of 6.77% to 19.65% (SSP119), 7.66% to 22.65% (SSP245), and 15.88% to 46.69% (SSP585), respectively, in the three scenarios relative to 2020; (2) The future supply and demand trends for the three scenarios of produced water services are similar, and the overall supply and demand risks are all on a downward trend. Water demand continues to decline, and by 2050, the water demand of the 3 scenarios will decrease by 96.275×108t, 81.210×108t, and 84.13×108t relative to 2020, respectively; while supply decreases from 2030 to 2040 and rises from 2040 to 2050; (3) Both water supply and demand distributions exhibit spatial correlation, and the distribution of hotspots is similar. The water supply and demand are well-matched, with an overall supply-demand ratio greater than 1.5; (4) LUCC can either increase or decrease water yield. Built-up land provides more water supply compared to other land types, while forest land has the lowest average water supply. Limiting land use type conversions can enhance the water supply.

Evaluating the Effects of Wetland Restoration on Ecosystem Services Using InVEST and Geostatistics: A Case Study of Dongting Lake in China

Ecological restoration projects aim to recover ecosystems that have been degraded, damaged, or destroyed. The effective assessment of these projects is crucial for ensuring that restoration goals are met and for guiding future efforts. The Poplar Ecological Restoration Project (PERP), focused on removing floodplain poplar plantations, is a key environmental initiative in China to preserve the ecological functions and services of the Dongting Lake freshwater wetland complex. Understanding the dynamic changes in ecosystem services and their trade-offs/synergies before and after the project is crucial for ensuring that ecosystem services are maintained and enhanced. This study selected three key ecosystem services, water conservation, carbon storage, and habitat quality, as indicators to assess the PERP. Using the Integrated Valuation of Ecosystem Services and Trade-offs (InVEST) model and geostatistical methods, including the Spearman correlation analysis and spatial autocorrelation analysis, we explored the ecological outcomes of the project. The results indicated that since its implementation in 2014, the PERP has significantly altered the land use and land cover (LULC) in the lake. Most of the former plantations have been converted into reedbeds (17,404 ha), followed by sedgelands (3841 ha), mudflats (443 ha), shallow waters (382 ha), and deep waters (301 ha). During this period, water conservation and habitat quality initially decreased and then increased, while carbon storage continuously declined. Overall, all assessed services showed an increasing trend except for carbon storage, resulting in a slight decrease in the integrated ecosystem services. Moreover, there were strong bivariate associations among the three investigated ecosystem services, and the synergies were strengthened during the project. Importantly, these synergies became positive after the PERP, meaning that the improvement of one service enhanced others, potentially leading to a more sustainable and resilient ecosystem.