ArticleScientific data2026
Multi-scale ecosystem service dataset for Southern Hilly Region of China (1990-2024).
Article in Scientific data, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
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Who cites it
1 citing paper in PubMed.
- Multi-scale ecosystem service dataset for Southern Hilly Region of China (1990-2024).Scientific data · 2026Article
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Authors and funding
5 authors.
Funding
Abstract
Ecosystem services are spatially heterogeneous and scale dependent, which makes long-term and cross-scale datasets essential for regional ecological assessment and environmental management. However, for the Southern Hilly Region of China (SHR), ecosystem service datasets that are temporally explicit, methodologically consistent, and organized across multiple watershed-based management scales remain limited. Here, we present a spatially explicit, multi-scale ecosystem service dataset for the SHR covering eight temporal snapshots from 1990, 1995, 2000, 2005, 2010, 2015, 2020 to 2024 at a base spatial resolution of 30 m. The dataset quantifies five key ecosystem services, namely water yield, nutrient delivery ratio, soil conservation, carbon storage, and habitat quality, using a unified workflow based on InVEST version 3.14.1. Ecosystem services were first generated as raster outputs and were subsequently aggregated to watershed and sub-watershed units within a consistent hierarchical spatial framework. Compared with existing ecosystem service products that are often national or global in scope, coarser in temporal detail, or not organized for watershed-based multi-scale analysis, this dataset provides a region-specific, high-resolution, and reusable product for long-term ecosystem service assessment in the SHR. All input layers were harmonized to a common spatial framework, annual land-cover and climate inputs were matched to the corresponding model years, and static soil, topographic, carbon-density, and habitat-sensitivity parameters were kept constant to support temporal comparability. The dataset has been deposited in Zenodo under the Creative Commons Attribution 4.0 International license and is available at https://doi.org/10.5281/zenodo.18329300
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Registered trials
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