The impact of impervious surface expansion morphology on ecosystem services and thresholds in the Haihe River basin

• Published in: Ecological indicators Vol. 175; p. 113493
• Main Authors: Gu, Yang, Chen, Yujia, Yang, Dongdong, Zhao, Xin, Pan, Shunqi
• Format: Journal Article
• Language: English
• Published: Elsevier Ltd 01.06.2025; Elsevier
• Subjects: analysis of variance; Basin planning; basins; carbon sequestration; Ecosystem services; ecosystems; habitats; Impervious surface areas; Nonlinear relationships; soil conservation; Sustainable development; water yield; watersheds; Nonlinear relationships; NP; PAFRAC; Impervious surface areas; SHAPE_MN; Sustainable development; ES; CES; ISEM; Basin planning; COHESION; ENN_MN; ISA; HRB; Ecosystem services; CA
• ISSN: 1470-160X
• DOI: 10.1016/j.ecolind.2025.113493

[Display omitted] •A threshold-based framework for sustainable basin planning was proposed.•The comprehensive ecosystem service guides the delineation of zoning.•Nonlinear relationships were assessed using restricted cubic splines.•Impervious surface expansion morphology exhibits significant regional differences. The rapid expansion of impervious surface areas (ISA) has a profound impact on basin ecosystem services (ES). However, the relationship between impervious surface expansion morphology (ISEM) and ES remains insufficiently studied. This study focused on the Haihe River Basin (HRB) and first quantified ISEM from three dimensions i.e. patch scale, shape complexity, and spatial aggregation. The InVEST model was then employed to assess ES, including habitat quality, carbon storage, water yield, and soil conservation, followed by the calculation of comprehensive ecosystem service (CES). Subsequently, GeoDetector and restricted cubic spline were employed to analyze the drivers, interactions, and threshold effects of ISEM on CES. Finally, an analysis of variance was conducted to identify ISEM profiles for regions with different CES levels, offering a basis for basin zoning and planning. The results indicated that: (1) All ISEM indicators had a significant impact on CES. Notably, during the period from 2002 to 2022, the euclidean nearest-neighbor distance mean (ENN_MN) showed the largest influence on CES, with q-values of 0.601, 0.586, and 0.561, respectively; (2) Except for mean shape index (SHAPE_MN), other ISEM indicators showed significant nonlinear relationships with CES (p < 0.001), with their impact on CES changing after exceeding certain thresholds; and (3) ISEM profiles exhibited contrasting differences between regions with high and low CES.