Integrated Valuation Of Ecosystem Services And Tradeoffs Model Research Articles

A Multi-Objective Scenario Study of County Land Use in Loess Hilly Areas: Taking Lintao County as an Example

Land use serves as a connecting link between human activities and the natural ecology of the surface; under the multi-objective background of national policies and dual-carbon tasks, land use transformation is studied and simulated in multiple scenarios, and carbon stock changes are analyzed based on future land use to explore the path for a region to achieve multi-objective coordination. Drawing upon land use data from 2000 to 2020 in Lintao County, Gansu Province, we conducted an in-depth analysis of the dynamics governing land use transformation. Subsequently, employing the FLUS (Future Land Use Simulation) model, we simulated the projected land use for Lintao County in 2035 under various scenarios. Furthermore, we utilized the InVEST (Integrated Valuation of Ecosystem Services and Trade-offs) model to assess the change in carbon stock within the study area under each scenario. These analyses aim to furnish a robust scientific foundation for future land use planning endeavors in Lintao County. The conclusions are as follows: (1) The land use transition in Lintao County from 2000 to 2020 showed the strongest motivation for construction land growth, with continued rapid growth in the scale of urban land and other construction land and relatively slow growth in the land for rural settlement areas, while cropland and water areas continued to decrease, forest land grew slowly, the magnitude of land use change exhibited a higher intensity in river townships compared with mountainous townships. (2) The simulation results of cropland protection scenario (CPS), ecological protection scenario (EPS), economic development scenario (EDS), and comprehensive development scenario (CDS) in 2035 are better. Among them, the CDS, which considers various types of higher-level strategic requirements and can compensate for the single-goal nature of the single-demand scenario, demonstrates a higher level of rationality in the land use pattern. (3) The total carbon stock in descending order is the EPS, CDS, EDS, and CPS. Among these, the CDS is at a higher level of total carbon stock, and the changes in carbon stock in each land use site are more balanced, which is an ideal carbon stock state and a scenario more in line with multi-objective coordination.

Coupling and Coordination Relationship of Economic–Social–Natural Composite Ecosystem in Central Yunnan Urban Agglomeration

Exploring the spatio-temporal differentiation characteristics and coupling coordination relationship of the composite ecosystem of urban agglomerations is of great significance for promoting the synergistic sustainable development and integration construction of urban agglomerations. This paper is based on LUCC (Land Use and Land Cover Change) data, a DEM (Digital Elevation Model), and temperature, precipitation, and other multi-source data, using the central Yunnan urban agglomeration as an example and constructing a multi-dimensional evaluation index system highlighting development quality and efficiency. The entropy weight method was first used to determine the comprehensive weights to evaluate the regional economic and social development level. Then, the InVEST (Integrated Valuation of Ecosystem Services and Trade-offs) model was used to quantitatively calculate and analyze the spatial and temporal evolution characteristics of the four key ecosystem services, evaluating the spatio-temporal evolution characteristics of the natural subsystem. The coupling coordination model was used to quantitatively analyze the evolution of the coupling coordination of the composite ecosystems in the central Yunnan urban agglomeration during the period of 2010–2020, and to reveal its development law. The results show the following: ➀ During the study period, the socio-economic subsystems in the central Yunnan urban agglomeration demonstrated an outward radiative growth from Kunming City, marked by underdeveloped sub-centers and prevalent low-level areas. ② Trends in ecosystem services varied, with water and soil conservation showing fluctuating increases, carbon sequestration remaining stable, and habitat quality declining. The critically important integrated ecosystem services zone of the natural subsystem is mainly located in the northeastern region and southwestern edge of the study area. ③ In 2020, the coupling coordination degree of the composite ecosystem was 0.9492. This showed that economic, social, and ecological subsystems are highly coupled, with consistent overall development trends and strong interactions. ④ The increase in the degree of harmonization amounted to 7.82%, with lagging subsystems varying in the degree of harmonization in subregions. This study can provide a scientific foundation for the development of policies for the Central Yunnan urban agglomeration, promoting regional sustainable development and optimizing the spatial pattern of the national territory.

Analysis and Simulation of Land Use Changes and Their Impact on Carbon Stocks in the Haihe River Basin by Combining LSTM with the InVEST Model

The quantitative analysis and prediction of spatiotemporal patterns of land use in Haihe River Basin are of great significance for land use and ecological planning management. To reveal the changes in land use and carbon stock, the spatial–temporal pattern of land use data in the Haihe River Basin from 2000 to 2020 was studied via Mann–Kendall (MK) trend analysis, the transfer matrix, and land use dynamic attitude. Through integrating the models of the Integrated Valuation of Ecosystem Services and Trade-offs (InVEST) and the Long Short-Term Memory (LSTM), the results of the spatial distribution of land use and carbon stock were obtained and compared with Cellular Automation (CA-Markov), and then applied to predict the spatial distribution in 2025. The results show the following: (1) The land use and land cover (LULC) changes in the Haihe River Basin primarily involve an exchange between cultivated land, forest, and grassland, as well as the conversion of cultivated land to built-up land. This transformation contributes to the overall decrease in carbon storage in the basin, which declined by approximately 1.20% from 2000 to 2020. (2) The LULC prediction accuracy of LSTM is nearly 2.00% higher than that of CA-Markov, reaching 95.01%. (3) In 2025, the area of grassland in Haihe River Basin will increase the most, while the area of cultivated land will decrease the most. The spatial distribution of carbon stocks is higher in the northwest and lower in the southeast, and the changing areas are scattered throughout the study area. However, due to the substantial growth of grassland and forest, the carbon stocks in the Haihe River Basin in 2025 will increase by about 10 times compared with 2020. The research results can provide a theoretical basis and reference for watershed land use planning, ecological restoration, and management.

Geospatial mapping of carbon estimates for forested areas using the InVEST model and Sentinel-2: A case study in Galicia (NW Spain)

CO2 emissions have increased exponentially in recent years, so measuring and quantifying carbon sequestration is a step towards sustainable forest management and combating climate change. The overall goal of this study is to develop an accurate model for estimating carbon storage and sequestration for forest areas of the Atlantic Biogeographic Region. Specifically, the modelling and field sampling are carried out in the municipality of Baiona (Galicia, NW Spain), which was selected as a representative biome of this region. The methodology consists of carrying out two object-based image analysis (OBIA) classifications in spring and autumn to observe possible stocks of seasonal differences. Two carbon storage and sequestration models are built up (model 1 and model 2): model 1 for forest areas only and model 2 including all other land cover in the study area. Sentinel-2 geospatial data for 2021, Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) tools and geographic information systems (GIS) are used. A Kappa index of 0.92 is obtained for both classifications, thus ruling out any notable seasonal differences in the images used. The results from both models indicate that it is land covers associated with forest uses which store the most carbon in the study area, accounting for >50 % more than the other land covers. It is concluded that the methodology and data used are very useful for quantifying ecosystem services, which will help the governance of the region by implementing measures to mitigate some of the effects of climate change and help to create silvicultural models for the sustainable management of the Atlantic Biogeographic Region.

Factor analysis of hydrologic services in water-controlled grassland ecosystems by InVEST model and geodetector.

Water conservation is highly important for a successful desert grassland ecosystem, but there was no comprehensive view on how to assess influencing factors in managing and addressing water yield and water conservation in desert steppe. The Integrated Valuation of Ecosystem Services and Trade-offs (InVEST) model, which is specifically used for the assessment of ecosystem services, was combined with geographic detectors to identify the priority areas for water conservation function and analyze the driving factors of water conservation in the Tabu River Basin, Inner Mongolia Autonomous Region, China, using different meteorological data sources. (i) The InVEST model has the advantage of modeling water yield and water conservation at spatial scales by fusion downscaling data. High water yield mainly occurs in the southern hilly mountainous areas, low water yield in the northern desert and grassland areas, and between the two in the central agro-pastoral areas; the multi-year average water conservation and water yield based on the InVEST model are 3.3 and 16mm, respectively. (ii) Water yield and water conservation roughly show a transitional phenomenon of "high in the south and low in the north." The water yield and water conservation per unit area of the Tabu River Basin are relatively large for construction land, unused land, and cropland, relatively small for grassland and forestland, and basically zero for water bodies. Forest land has the strongest water conservation capacity, followed by grassland and farmland, while the order of water yield capacity is the opposite. (iii) Precipitation shows the strongest explanatory power for water yield (q = 0.427), followed by land use types (q = 0.411). The precipitation ∩ actual evapotranspiration has the strongest explanatory power for water yield (q = 0.87). The explanatory power of water yield on water conservation is the strongest (q = 0.752), followed by precipitation (q = 0.4), and the water yield ∩ soil has the greatest explanatory power on water conservation (q = 0.91). These findings are crucial for promoting regional hydrologic services and can provide a water resources management strategy for decision-makers.

Riparian habitat quality as an indicator of land use/land cover effects on riverine water quality

Riparian land use/land cover (LULC) plays a crucial role in maintaining riverine water quality by altering the transport of pollutants and nutrients. Nevertheless, establishing a direct relationship between water quality and LULC is challenging due to the multi-indicator nature of both factors. Water quality encompasses a multitude of physical, chemical, and biological parameters, while LULC represents a diverse array of land use types. Riparian habitat quality (RHQ) serves as an indicator of LULC. Yet, it remains to be seen whether RHQ can act as a proxy of LULC for assessing the impact of LULC on riverine water quality. This study examines the interplay between RHQ, LULC and water quality, and develops a comprehensive indicator to predict water quality. We measured several water quality parameters, including pH (potential of hydrogen), TN (total nitrogen), TP (total phosphorus), Twater (water temperature), DO (dissolved oxygen), and EC (electrical conductivity) of the Yue and Jinshui Rivers draining to the Han River during 2016, 2017 and 2018. The water quality index (WQI) was further calculated. RHQ is assessed by the InVEST (Integrated Valuation of Ecosystem Services and Tradeoffs) model. Our study found noticeable seasonal differences in water quality, with a higher WQI observed in the dry season. The RHQ was strongly correlated with LULC compositions. RHQ positively correlated with WQI, and DO concentration and vegetation land were negatively correlated with Twater, TN, TP, EC, cropland, and construction land. These correlations were stronger in the rainy season. Human-dominated land, such as construction land and cropland, significantly contributed to water quality degradation, whereas vegetation promoted water quality. Regression models showed that the RHQ explained variations in WQI better than LULC types. Our study concludes that RHQ is a new and comprehensive indicator for predicting the dynamics of riverine water quality.

Evaluation of the water conservation function in the Ili River Delta of Central Asia based on the InVEST model

The Ili River Delta (IRD) is an ecological security barrier for the Lake Balkhash and an important water conservation area in Central Asia. In this study, we selected the IRD as a typical research area, and simulated the water yield and water conservation from 1975 to 2020 using the water yield module of the Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) model. We further analyzed the temporal and spatial variations in the water yield and water conservation in the IRD from 1975 to 2020, and investigated the main driving factors (precipitation, potential evapotranspiration, land use/land cover change, and inflow from the Ili River) of the water conservation variation based on the linear regression, piecewise linear regression, and Pearson’s correlation coefficient analyses. The results indicated that from 1975 to 2020, the water yield and water conservation in the IRD showed a decreasing trend, and the spatial distribution pattern was “high in the east and low in the west”; overall, the water conservation of all land use types decreased slightly. The water conservation volume of grassland was the most reduced, although the area of grassland increased owing to the increased inflow from the Ili River. At the same time, the increased inflow has led to the expansion of wetland areas, the improvement of vegetation growth, and the increase of regional evapotranspiration, thus resulting in an overall reduction in the water conservation. The water conservation depth and precipitation had similar spatial distribution patterns; the change in climate factors was the main reason for the decline in the water conservation function in the delta. The reservoir in the upper reaches of the IRD regulated runoff into the Lake Balkhash, promoted vegetation restoration, and had a positive effect on the water conservation; however, this positive effect cannot offset the negative effect of enhanced evapotranspiration. These results provide a reference for the rational allocation of water resources and ecosystem protection in the IRD.

Spatio-temporal variation in soil erosion on sloping farmland based on the integrated valuation of ecosystem services and trade-offs model: A case study of Chongqing, southwest China

Mastering the spatio-temporal evolution of soil erosion on regional sloping farmland is crucial for optimizing erosion control planning and carrying out soil quality evaluations. To simulate the potential or net soil erosion on sloping farmland in Chongqing, China, this study analyzed the temporal and spatial variation features of soil erosion using the integrated valuation of ecosystem services and trade-offs (InVEST) model and other models. The InVEST model was applied to calculate the soil erosion modulus on sloping farmland, hotspot analysis was used to identify hot and cold spots of sloping farmland erosion, and the chord diagram visualization model was used to reflect the transformation quantity and flow direction relationship between different erosion levels of sloping farmland transfer processes in different periods. The results showed that soil erosion on sloping farmland in Chongqing presents a distribution pattern of high values of soil erosion in the northeast and low values in the southwest. Very strong and severe erosion is concentrated in the low mountainous hilly areas in the northeast and southeast of Chongqing, while slightly and lightly eroded areas are distributed in the western and central flatter areas. The soil erosion grade of most sloping farmland is light and middle; in addition, the annual average soil erosion modulus shows a decreasing trend. Only in 2000 was it in the middle erosion grade. The areas with strong, very strong and severe erosion showed a downward trend, with the proportion decreasing from 18 % to 11 %. The average erosion modulus with slope > 25° was the largest (7553 t·km−2·a-1) and presented strong erosion. Soil erosion in sloping farmland mainly occurs between 400 and 1600 m of elevation. This research can effectively improve soil erosion control and quality control of sloping farmland and provide a reference for the sustainable development of land use in the region.

As green infrastructure, linear semi-natural habitats boost regulating ecosystem services supply in agriculturally-dominated landscapes

Semi-natural linear landscape elements, such as hedgerows, are vital structures within agricultural landscapes that have an impact on ecosystem processes and support biodiversity. However, they are typically omitted from green infrastructure planning, which could lead to significant undervaluing of landscapes and their multifunctionality in terms of ecosystem service supply. Using the InVEST (Integrated Valuation of Ecosystem Services and Tradeoffs) model suite, we tested the effects of additionally including semi-natural linear landscape elements on the model outcomes for crop pollination, nutrient regulation, erosion regulation and water flow regulation ecosystem services supply. The results showed that linear semi-natural landscape elements contribute positively to the landscape’s multifunctionality. Small changes have been identified for water flow regulation, whereas, considering both spatial extent and magnitude of the changes, the greatest changes have been found with respect to the supply of pollination and nutrient regulation. Direct proximity of the linear elements had the greatest effect on ecosystem service supply, in particular with regard to pollination. Based on our results, a more pronounced consideration of semi-natural linear landscape elements as an important element of green infrastructure is advisable.

Simulation and analysis of ecological early-warning of urban construction land expansion based on digital sensing feature recognition and remote sensing spatial analysis technology

To improve the analysis effect of the simulation and prediction of the expansion effect of urban construction land, this paper combines the digital sensing feature recognition and remote sensing analysis technology for the earth's surface, and uses Artificial-neural-network-based cellular automaton (ANN-CA) Markov model and Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) model to study and analyze the expansion effect and trend of urban construction land, and subdivides the spatial and temporal characteristics of land cover. In addition to that, multi-based sensing data is used to generate urban construction land expansion effect drivers. The multi-source sensing data and InVEST model are used to conduct spatial information analysis and ecological early-warning. The research shows that combining digital sensing feature identification and remote sensing analysis technology, using the analysis model of ANN-CA-Markov model and InVEST model can effectively improve the analysis effect of urban construction land expansion effect prediction, and carry out ecological early-warning of construction land expansion on this basis. Overall territorial spatial planning stage of Xuzhou city, the designated ecological space area accounts for 20% of the whole land area. There is a sharp contradiction between constructive land expansion and ecological security in the whole region, so it is appropriate to conduct precise intervention and efficient management of constructive land expansion according to ecological early-warning.

Spatiotemporal evolution and multi-scenario prediction of habitat quality in the Yellow River Basin

IntroductionThe Yellow River Basin (YRB) is not only a vital area for maintaining ecological security but also a key area for China’s economic and social development. Understanding its land-use change trends and habitat quality change patterns is essential for regional ecological conservation and effective resource allocation.MethodsThis study used the patch-generating land-use simulation (PLUS) and Integrated Valuation of Ecosystem Services and Trade-offs (InVEST) models to analyze and predict the spatial and temporal trends of habitat quality in the YRB from 2000 to 2030 under natural development (ND) and ecological conservation and high-quality development (ECD) scenarios. The PLUS model was used to predict land-use change in 2030 under different scenarios, after which the InVEST model was used to obtain the habitat quality distribution characteristics from the 2000–2030 period.Results(1) The mean values of habitat quality in the YRB in 2000, 2010, and 2020 were 0.6849, 0.6992, and 0.7001, respectively. The mean habitat quality values were moderately high. Spatial distribution characteristics were high in the west and low in the east and along the water. In 2030, habitat quality (0.6993) started to decline under ND, whereas under ECD, there was an indication of substantial improvement in habitat quality (0.7186). (2) The mean habitat degradation values in 2000, 2010, and 2020 were 0.0223, 0.0219, and 0.0231, respectively. The level of habitat degradation showed a decreasing trend, followed by an increasing trend with a stable spatial distribution pattern. The mean level of habitat degradation in 2030 (0.0241) continued to increase under ND, while a substantial decrease in the level of habitat degradation occurred under ECD (0.0214), suggesting that the level of habitat degradation could be effectively contained under the ECD scenario. (3) During the study period, the conversion of building land—both negative and positive—had the most pronounced impact on habitat quality per unit area. Further, the conversion of grassland was shown to be a key land transformation that may either lead to the deterioration or improvement of the ecological environment. The results provide scientifific theoretical support and a decision basis for ecological conservation and the high-quality development of the YRB.

Improvement of water yield and net primary productivity ecosystem services in the Loess Plateau of China since the “Grain for Green” project

The Loess Plateau of China is one of the regions with the most serious soil erosion globally. The ambitious “Grain for Green” project was there implemented to restore degraded ecosystems, profoundly changing the water yield and carbon sequestration ecosystem services. To understand the changes of water- and carbon-related ecosystem services (hereafter WCES) in the Loess Plateau, this study combined the CASA (Carnegie-Ames-Stanford Approach) model and InVEST (Integrated Valuation of Ecosystem Services and Trade-offs) model to thoroughly reveal the changes and intrinsic linkages of water yield and net primary productivity since the “Grain for Green” project in the Loess Plateau. The results show that the WCES of the Loess Plateau were increasing since 2001, dominated by both the climate change and human afforestation. The water yield and net primary productivity showed strong synergistic effects in 80% of the Loess Plateau, mainly resulting from the rapid increase of precipitation in recent years. The increasing atmospheric precipitation contributed to more WCES provisions, which may have offset the trade-off between WCES caused by large-scale afforestation. In view of the synergistic effects of WCES, enhancing water input into the ecosystem may be an effective measure to respond with future WCES degradation in dry years, such as artificial basin-cross water transfer project. Despite the low correlation between teleconnection factors and WCES, the low water yield and reduction of net primary productivity may be associated with a strong El Niño event in 2015. This study assists in a wise decision-making on the future “Grain for Green” and ecological management in the Loess Plateau.

Effects of Temporal and Spatial Changes in Wetlands on Regional Carbon Storage in the Naoli River Basin, Sanjiang Plain, China

The Naoli River (NLR) Basin is a crucial distribution area for wetlands in China. Investigating the link between land use changes and carbon storage in this basin is of significant importance for protecting regional ecosystems and promoting the sustainable development of the social economy. This paper uses long-term Landsat satellite images provided on the GEE (Google Earth Engine) platform and the random forest classification algorithm to create spatial distribution maps of land use in the NLR Basin from 1993 to 2022. The study analyzes the dynamic changes in wetlands in the basin over the past 30 years and employs the InVEST (Integrated Valuation of Ecosystem Services and Tradeoffs) model to explore the temporal and spatial evolution characteristics of carbon storage. The results reveal that the wetland area of the NLR Basin showed a downward trend from 1993 to 2022, with a total decrease of 1507.18 hm2 over 30 years. During this period, the carbon storage in the NLR Basin decreased, with a cumulative loss of 1.98 × 107 t, mainly due to the continuous reductions in wetland and forest land. Additionally, the change in carbon storage in the basin has a strong spatial and temporal relationship with the changes in land use/cover area. The total carbon storage is positively associated with the areas of wetland, forest land, and water bodies. The conversion of wetlands into any other land type results in the reduction in carbon storage. These findings can improve our understanding of the spatial and temporal dynamics of wetlands in the NLR Basin over the past 30 years and enable us to analyze the relationship between land use changes and regional carbon storage. The results of this study have great significance for protecting the wetland ecology and regional carbon balance in the NLR Basin.

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.

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.

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.

Quantity and spatial imbalance of supply and demand for water yield services in terrestrial ecosystems under different future land use scenarios in Xinjiang, China

Drylands in northwest China have limited water resources, which negatively impacts economic development, ecological security, and the United Nations Sustainable Development Goals. However, few studies have examined water supply and demand under multiple future spatial patterns of land use, particularly under sustainable development scenarios. Further research is therefore needed to determine how affect water output services under various land use patterns. We used the GMOP-PLUS (Gray Multi-objective Optimization-Patch-generating Land Use Simulation) and the InVEST (Integrated Valuation of Ecosystem Services and Tradeoffs) models to investigate future land use programs and the current and future trends in water yield services supply and demand in the typical dryland region of Xinjiang, China. The GMOP-PLUS model was used to project the spatial patterns of land use/land cover (LULC) change in Xinjiang in 2025 and 2030 under programs of business-as-usual, rapid economic development, ecological land protection and sustainable development. We then used the InVEST model to project the spatiotemporal evolution of water yield services supply and demand under the four different scenarios. Our results show that Our results show that water production in Xinjiang decreases to 911.30 × 108 m3 in 2020–2030 under the business-as-usual scenario, with an expansion in arable land and a reduction in forested land being the main causes of this decrease. The decline in water production under the ecological land protection scenario is 913.88 × 108 m3. The retention effect of vegetation slows the decline in water production, but the ecological land protection scenario is not effective in controlling the reduction in arable land. The rapid economic development scenario produces a significant increase in water yield of 915.09 × 108 m3, mainly due to an increase in the area of impervious surfaces caused by the expansion of built-up land; however, the rapid economic development scenario leads to a decreasing trend in ecological land. The sustainable development scenario produces 914.15 × 108 m3 of water. The sustainable development scenario increases water production while balancing the development of Constructed and the protection of ecological land, and the arable land also shows a slow growth trend. Between 2025 and 2030, the water security index fluctuates between –0.0225 and –0.0400, with a continued future deficit in water supply and demand in Xinjiang and a high degree of spatial heterogeneity. Programs for advancing sustainable development narrow the supply–demand gap for services that produce water.

Scenario modeling to predict changes in land use/cover using Land Change Modeler and InVEST model: a case study of Karaj Metropolis, Iran

Models for land cover/land use simulation are appropriate and important tools for decision-makers, helping them build future plausible landscape scenarios. Due to the fact that the simulation results of different models may be different, it is sometimes difficult for users to choose a suitable model. Therefore, in this study, an integrated approach is used, combining the data obtained from remote sensing and GIS with Land Change Modeler (LCM) and Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) models to simulate and predict land cover/land use changes for 2028 in Karaj metropolis (Northern Iran as a poor region-in terms of data-which is under intense and rapid urbanization. In this sense, three land cover/land use maps related to the study area were primarily generated using satellite image data for the period 2006, 2011, and 2017. They were used as a basis to define two scenarios: business-as-usual (BAU) scenario and participatory plausible scenario (PPS) for 2028. Afterwards, the necessary input data used in running of both models were prepared and, then, the outputs of the models were interpreted and compared. According to the results, while human-made coverage and low-density grasslands increased by about 74% and 12%, respectively, it was from 2006 to 2017 that agricultural lands, gardens, and high-density grasslands decreased by 42%, 34%, and 7%, respectively. According to the business-as-usual scenario, which was projected using the LCM model, the increase in human-made cover will continue by about 29% by 2028, and the reduction rate of agricultural lands, gardens, and low-dense and dense grasslands will experience decrease by about 20%, 3%, 11%, and 9%, respectively. The participatory plausible scenario for 2028, which was defined using the InVEST model, confirmed the same results, but having different quantities. Accordingly, while human-made cover will increase by about 73%, the reduction rate of agricultural lands, gardens, and low-dense and dense grasslands will decrease by about 41%, 10%, 16%, and 1%, respectively. The output quantities of InVEST scenario model seem to be closer to reality with less uncertainty, because this model estimates the quantity of demand for land and its suitability for different uses, based on the views of different stakeholders, and considers landscape development future policies and plans. In contrast, the LCM model is based solely on trend extrapolation from the past to current time and changes in the landscape structure.

Coupling PLUS–InVEST Model for Ecosystem Service Research in Yunnan Province, China

In efforts to improve regional ecosystem service functions, coordinate land development and ecological conservation, and establish a reference for optimizing land resource allocation and policy formulation to cope with climate change, it is critical to investigate the spatial distribution of land use/cover change (LUCC) and ecosystem services (ESs) under future climate change. This study proposes a framework based on the Shared Socioeconomic Pathway and Representative Concentration Pathway (SSP-RCP), integrating the patch-generating land use simulation (PLUS) model and the integrated valuation of ecosystem services and tradeoffs (InVEST) model to analyze the spatial agglomeration of ESs, to analyze the importance of each driving factors. The results of the study show as follows: (1) the combination of CMIP6 and PLUS models can effectively simulate land use with an overall accuracy of 0.9379. (2) In spatial correlation, ESs show good clustering in all three future scenarios, with similar distribution of cold hotspots in the SSP126 and SSP245 scenarios. Hotspots are more dispersed and cold spots are shifted to the west in the SSP585 scenario. (3) GDP is an important factor in carbon storage and habitat quality, and precipitation has a greater impact on soil retention and water production. Overall, ESs can be increased by appropriately controlling population and economic development, balancing economic development and ecological protection, promoting energy transition, maintaining ecological hotspot areas, and improving cold spot areas.

Effect of land use change on carbon stocks in an agricultural region of southern Benin

AbstractLand use change is one of the most important determinants of carbon storage and dynamics in ecosystems. Areas in the proximity of metropoles undergo land use changes but are poorly studied for their soil and biomass carbon budget, especially in Africa. Close to Benin's economic capital, the Lama Territory located on the Allada Plateau and is subject to high demographic and urbanization pressures. Carbon (C) stocks in the region are likely to be rapidly changing. This research assessed the land use changes and quantified the spatial distribution and variation of C stocks between 2000 and 2018 on the Ferralsols of the study area. Random forest models using spectral bands of LANDSAT images and some spectral indices as predictors were calibrated to classify the land use. C stocks of four C pools (aboveground, belowground biomass, litter, and soil) were mapped with InVEST (integrated valuation of ecosystem services and tradeoffs) model. Land use change occurred in 61% of the Ferralsol area between 2000 and 2018. The surface of forests and crop‐plantation associations decreased in benefit of tree plantations, adult palm groves, and built‐up areas. With the loss of forest surface and the increasing urbanization, C stocks of the region decreased by −218 Gg C with 4% uncertainty (−175 Gg C in soil pools, and − 125 Gg C in aboveground biomass with both 6% uncertainty) between 2000 and 2018. Results highlight: (i) the need for soil C stock accounting to avoid underestimation of C stocks evolution in a rural region; and (ii) the relevance of tree plantations and deforestation control to maintain the C stocks in tropical areas.