How to Detect Scale Effect of Ecosystem Services Supply? A Comprehensive Insight from Xilinhot in Inner Mongolia, China

Multiscale Characteristics and Drivers of the Bundles of Ecosystem Service Budgets in the Su-Xi-Chang Region, China

Managing ecosystem services (ESs) to meet human needs is critical to achieving sustainable development in rapidly urbanizing regions. Identifying ES budget bundles and analyzing their drivers at a multiscale level can facilitate management decision-making; however, further research is required in areas undergoing rapid urbanization. This study quantified the supply, demand, and budgets of six typical ESs at the county, township, and village scales in the Su-Xi-Chang region in 2020. Additionally, the influence of natural environmental and socioeconomic factors on ES budget bundles was investigated based on K-means cluster analysis and the Geodetector model. The results showed that ESs on all three scales showed a mismatch between supply and demand. The similarity in the spatial pattern of supply, demand, and budgets of ESs at the township and village scales was higher than that at the township and county scales. The location and area of surplus, balance, and deficit varied with scale. We found that population density and the proportion of impervious surfaces are the main factors influencing the formation of the ES budget bundles at different scales. In addition, the diversity and degree of interpretation of drivers varied with scale. We believe that focusing on the overall situation on a large scale and implementing precise management on a small scale can make management decisions more effective. This study can provide a scientific basis for the sustainable utilization of ESs in the Su-Xi-Chang region, and the research results and methods can provide a reference for similar studies in other rapidly urbanizing areas in the world.

Trade-off among grain production, animal husbandry production, and habitat quality based on future scenario simulations in Xilinhot

The balance and optimization of ecosystem services (ESs) are the basis of spatial planning and ecological landscape design. Selecting suitable ESs and developing integrated, quantitative, and spatially explicit assessment models is the key to balance research. In Xilinhot in eastern Inner Mongolia, China, grain production, animal husbandry production, and habitat quality are key ESs that affect the livelihoods of local farmers and herders and the regional ecological balance. Based on GlobeLand30 data for 2000-2020, we designed six future land scenarios for the region and used the future land use simulation (FLUS) model to simulate the land use/cover scenarios in 2030. Then, we analyzed staple grain production (SGP), sustainable stocking capacity (SSC), and habitat quality (HQ) under each scenario, and constructed a multi-ES comprehensive trade-off method, using the comprehensive trade-off score (CTS) to measure their overall development quality. The results show the following. (1) Under various scenarios, the SGP is negatively correlated with SSC and HQ, and the SSC is positively correlated with HQ. (2) In the inertial development scenario, the economic development priority scenario, and the quality habitat protection scenario, the SGP will increase, the SSC and HQ will decrease; among these scenarios, the economic development priority scenario is the most significant; their CTSs are 0.97, 0.95, and 0.98, respectively. In the ecological comprehensive governance scenario, the SSC will increase, SGP and HQ will decrease, and CTS is 0.98. (3) Based on the comprehensive trade-off analysis, the economic and ecological coordination scenario is the most beneficial for regional sustainable development. It achieves the stability of the SGP; although the SSC decreases slightly, the negative impact can be offset by a larger improvement in HQ. This paper provides clear policy suggestions for regional development, and the methodological framework we have constructed provides a reference for the study of complex land scenario simulations and multi-ecosystem service comprehensive trade-offs.

Assessment Method and Scale of Observation Influence Ecosystem Service Bundles

The understanding of relationships between ecosystem services and the appropriate spatial scales for their analysis and characterization represent opportunities for sustainable land management. Bundles have appeared as an integrated method to assess and visualize consistent associations among multiple ecosystem services. Most of the bundle assessments focused on a static framework at a specific spatial scale. Here, we addressed the effects of applying two cluster analyses (static and dynamic) for assessing bundles of ecosystem services across four different scales of observation (two administrative boundaries and two sizes of grids) over 13 years (from 2000 to 2013). We used the ecosystem services matrix to model and map the potential supply of seven ecosystem services in a case study system in the central high-Andean Puna of Peru. We developed a sensitivity analysis to test the robustness of the matrix. The differences between the configuration, spatial patterns, and historical trajectories of bundles were measured and compared. We focused on two hypotheses: first, bundles of ecosystem services are mainly affected by the method applied for assessing them; second, these bundles are influenced by the scale of observation over time. For the first hypothesis, the results suggested that the selection of a method for assessing bundles have inferences on the interactions with land-use change. The diverse implications to management on ecosystem services support that static and dynamic assessments can be complementary to obtain better contributions for decision-making. For the second hypothesis, our study showed that municipality and grid-scales kept similar sensitivity in capturing the aspects of ecosystem service bundles. Then, in favorable research conditions, we recommend the combination of a municipal and a fine-grid scale to assure robustness and successfully land-use planning processes.

Comprehensive Grassland Degradation Monitoring by Remote Sensing in Xilinhot, Inner Mongolia, China

Grassland degradation is a complex process and cannot be thoroughly measured by a single indicator, such as fractional vegetation cover (FVC), aboveground biomass (AGB), or net primary production (NPP), or by a simple combination of these indicators. In this research, we combined measured data with vegetation and soil characteristics to establish a set of standards applicable to the monitoring of regional grassland degradation by remote sensing. We selected indicators and set their thresholds with full consideration given to vegetation structure and function. We optimized the indicator simulation, based on which grassland degradation in the study area during 2014–2018 was comprehensively evaluated. We used the feeding intensity of herbivores to represent the grazing intensity. We analyzed the effects of climate and grazing activities on grassland degradation using the constraint line method. The results showed degradation in approximately 69% of the grassland in the study area and an overall continued recovery of the degraded grassland from 2014 to 2018. We did not identify any significant correlation between temperature and grassland degradation. The increase in precipitation promoted the recovery of degraded grassland, whereas increased grazing may have aggravated degradation. Our findings can not only improve the scientific quality and accuracy of grassland degradation monitoring by remote sensing but also provide clear spatial information and decision-making help in sustainable management of grassland regions.