Global Spatio‐Temporal Assessment of Changes in Multiple Ecosystem Services Under Four IPCC SRES Land‐use Scenarios

Abstract

Social development and technological advancement have led to land use changes, influencing the structure of ecosystem services and severely impacting ecological balance. This study spatially and quantitatively assesses the effects of land-use changes on ecosystem services based on the fourth assessment report of the Intergovernmental Panel on Climate Change (IPCC) and using the Integrated Valuation of Ecosystem Services and Tradeoff (InVEST) model. This model, applied on a global scale, was used to quantify the changes in three ecosystem services, namely, carbon storage, water yield, and sediment retention, 2010 and 2100 under four land use scenarios (A1B, A2, B1, and B2) and to evaluate the impact of land use changes to these services. The results indicate that (1) sediment retention and carbon storage under scenario B1 increase more than under other scenarios, with average global increases of 175.74 t/km 2 and 913.60 Mg/km 2 , respectively; water yield increase only under scenario A2 between 2010 and 2100, with average global increase of 3.51 mm; (2) forest and grassland are the principal land types providing three ecosystem services globally, and decreasing the area of barren contributes to increases in three ecosystem services; and (3) when barren is converted to forest, grassland, cropland, and urban, ecosystem services all increase, strengthening the utilization of barren land can increase ecosystem services greatly. This study provides a reference for further research and the sustainable development of ecosystem services. Plain Language Summary Analyzing the effects of land use changes on ecosystem services on a global scale is vital for the promotion of the sustainable development of ecosystems, especially in little-studied areas. Many studies have mapped and analyzed ecosystem services, but most have considered only local regions. There is no global research on this subject using IPCC SRES scenarios. This study aims to predict how different development scenarios (A1B, A2, B1, and B2) affect land use changes and to analyze the impact of corresponding land use changes on the ecosystem services of carbon storage, water yield, and sediment retention from a global perspective. We found that sediment retention and carbon storage under scenario B1 increased more than under other scenarios, with average global increases of 175.74 t/km 2 and 913.60 Mg/km 2 , respectively; water yield increased only under scenario A2 between 2010 and 2100, with average global increase of 3.51 mm, when forest, grassland, cropland, and urban were converted to barren, all three ecosystem services increased, strengthening the utilization of barren land increased ecosystem services greatly.

Trade-Offs and Synergies of Multiple Ecosystem Services for Different Land Use Scenarios in the Yili River Valley, China

“…For the SR model, this stu previous studies have calculated that the soil and water conservation volume of River Valley (based on actual measurements) was 2.64 × 10 8 tons [53], which is con This effect may also be related to the amount of nitrogen retained by the vegetation, which is consistent with the findings of Sun [48]. In this study, WY and SR were positively correlated with synergistic effects, which is consistent with the findings of Sun and Shi [54]. When forests are converted to grassland, farmland, and construction land, they have greater evapotranspiration, retention, and evaporation than grasses or crops, thus reducing water production [64].…”

“…This effect may also be related to the amount of nitrogen retained by the vege which is consistent with the findings of Sun [48]. In this study, WY and SR were pos correlated with synergistic effects, which is consistent with the findings of Sun a [54]. When forests are converted to grassland, farmland, and construction land, the greater evapotranspiration, retention, and evaporation than grasses or crops reducing water production [64].…”

“…Because of the flat landscape, dense soil layers, and good drainage conditions in the plains of the watershed area, the vicinity of the Yili and Turks river watersheds are often reclaimed for cultivated and construction land [36]. In the 2030 BAU scenario, there was a minor expansion of cropland and construction land, which is consistent with the findings of previous studies [54]. The increase in construction led to an increase in regional impervious surface area, which further led to an increasing trend in regional WY (Figure 3).…”

Research Progress of Grassland Ecosystem Structure and Stability and Inspiration for Improving Its Service Capacity in the Karst Desertification Control

“…Ecological corridors are important links between the structure and function of a system, and grasslands can be used as buffer zones to improve the connectivity of ecological functions, allowing species to use corridors for long-distance dispersal or to provide shelter for some animal movements [ 129 ], thus maintaining and protecting biodiversity and improving the quality of their habitats [ 130 , 131 ]. At the same time, the spatial pattern of the landscape influences the magnitude of ecosystem service provision at the landscape scale through grassland use patterns and connectivity [ 132 , 133 , 134 , 135 ]. By quantifying inter-annual and seasonal changes in grassland landscape patterns in northern China, Hao et al showed that degraded vegetation can influence changes in ecosystem service functions by changing land use patterns, increasing or dividing patch sizes of grassland and agricultural land, and increasing the size of forest areas where appropriate [ 136 ].…”

Exploring the spatiotemporal changes in carbon storage under different development scenarios in Jiangsu Province, China

“…Analyzing the demands of different cities could help policymakers choose an optimal urbanization model and land use pattern for improving CS ( Gao & Wang, 2019 ; Nie et al, 2020 ). Scenario settings are useful tools for predicting the future impacts of LULC changes on CS and can be used to produce critical information for urban development and planning ( Sun & Shi, 2020 ; Tang et al, 2020 ). However, previous studies predicting changes in LULC have had some limitations.…”