Spatiotemporal Variation in Ecosystem Services and Their Drivers among Different Landscape Heterogeneity Units and Terrain Gradients in the Southern Hill and Mountain Belt, China

Abstract

Understanding the spatiotemporal heterogeneity of ecosystem services (ESs) and their drivers in mountainous areas is important for sustainable ecosystem management. However, the effective construction of landscape heterogeneous units (LHUs) to reflect the spatial characteristics of ESs remains to be studied. The southern hill and mountain belt (SHMB) is a typical mountainous region in China, with undulating terrain and obvious spatial heterogeneity of ESs, and was selected as the study area. In this study, we used the fuzzy k-means (FKM) algorithm to establish LHUs. Three major ESs (water yield, net primary productivity (NPP), and soil conservation) in 2000 and 2015 were quantified using the Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) model and Carnegie Ames-Stanford approach (CASA) model. Then, we explored the spatial variation in ESs along terrain gradients and LHUs. Correlation analysis was used to analyze the driving factors of ESs in each terrain region and LHU. The results showed that altitude and terrain niche increased along LHUs. Water yield and soil conservation increased from 696.86 mm and 3920.19 t/km2 to 1061.12 mm and 5117.90 t/km2, respectively, while NPP decreased from 666.95 gC/m2 to 648.86 gC/m2. The ESs in different LHUs differed greatly. ESs increased first and then decreased along LHUs in 2000. In 2015, water yield decreased along LHUs, while NPP and soil conservation showed a fluctuating trend. Water yield was mainly affected by precipitation, temperature and NDVI were the main drivers of NPP, and soil conservation was greatly affected by precipitation and slope. The driving factors of the same ES were different in different terrain areas and LHUs. The variation and driving factors of ESs in LHUs were similar to some terrain gradients. To some extent, LHUs can represent multiple terrain features. This study can provide important support for mountain ecosystem zoning management and decision-making.

Spatial heterogeneity of ecosystem services in response to landscape patterns under the Grain for Green Program: A case‐study in Kaihua County, China

“…In addition, some natural factors may have influenced ES and lacked a link to landscape patterns, but due to the subjective nature of GFGP, this response to changes in landscape patterns was captured. For example, SC is significantly affected by topography, and WY is closely related to precipitation (Ma et al, 2022; L. J. Wang, Ma, Jiang, et al, 2021). Moreover, the selection of ES may not be sufficiently comprehensive, for example, food production is not taken into account.…”

The Grain for Green Program Intensifies Trade-Offs between Ecosystem Services in Midwestern Shanxi, China

“…Previous studies have confirmed that there are obvious geographical differences in ESs [53,54]. It is difficult for the classic global regression to reflect the differences in the relationship between ES trade-offs and influencing factors in geographic space, and not fully reflect actual local processes [55].…”

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

“…Therefore, the InVEST model was selected in this study to evaluate the dynamic changes of CS. Many previous studies have focused on the evaluation of multiple ecosystem services ( Ma et al, 2021 ; Wang et al, 2021a ; Wang et al, 2021b ), including their trade-offs and synergies ( Chen et al, 2021 ; Howe et al, 2014 ; Nelson et al, 2009 ; Washbourne et al, 2020 ). However, spatiotemporal changes in CS at the provincial scale and future changes in CS have not been thoroughly studied, especially with regard to the development needs of different cities.…”