Data · dataset · 2025
Data from: Identifying wetland restoration gaps and priorities from the perspective of wetland seasonality
Listed in ScienceDB
Aim: Human activities have extensively altered wetland hydrology, which is critical to support wetland vegetation, biodiversity, and ecosystem services.
Description
Even though wetland hydrology is the local manifestation of landscape-scale processes, restoration activities are typically implemented at individual wetland scale and focus on maximizing restored area. In this study, we propose a landscape approach to identify restoration priorities from the perspective of wetland seasonality. Location: In this study, we used the mid North China Plain (MNCP), a key agricultural region covered by multiple types of wetlands, as a case study area. Time period: 1985, 2020
Methods
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Based on wetland datasets, the normalized difference vegetation index (NDVI), digital elevation model data, meteorological data, and the water availability (WA) index, we analyzed the relationship between wetland seasonality and NDVI, quantified changes in wetland seasonality over 35 years (1985–2020), and identified priorities for wetland restoration in the mid North China Plain (MNCP). Results: The results showed that the annual maximum NDVI was strongly correlated with wetland seasonality (linear fit across seasonality bins; see Methods/Results).
In addition to the loss and gain of seasonal water surface area, a marked alteration of the seasonality regimes during 1985–2020 was observed. The priority areas for wetland restoration were primarily found in the southern part, east coast, and central part of the MNCP. Based on the WA in the catchment area of a restorable patch, the WA index provides insight into the self-sustaining potential of wetland hydrology and can be used as an indicator to identify restoration priorities.
Links
Where it is published
- DOI doi.org/10.57760/sciencedb.24164 ↗
DOI / persistent id · from scidb cn
Catalogue records · 1
- OAI-PMH record scidb.cn/oai?verb=GetRecord&metadataPrefix=oai_dc&identifier=10.57760%2… ↗
metadata API · from scidb cn
Topics
- From keywords
- Earth & Environmental Science · Engineering · Humanities · Life Sciences · Social Science
- Inferred from text
- Hydrology 74%
Provenance · 1 source records, 10 field assertions
| Source | Key | Last seen | Raw |
|---|---|---|---|
| ScienceDB | 10.57760/sciencedb.24164 | 12 d ago | JSON v1 |
| Field | Assertion | Extractor | Evidence |
|---|---|---|---|
| concepts[field].anzsrc:group:3707 | enrichment · scidb cn | taxonomy-embedding@1.0.0 | title+keywords+description (74%) |
| concepts[field].local:field:earth-environmental | mapping · scidb cn | connector:scidb_cn@1.0.0 | |
| concepts[field].local:field:engineering | mapping · scidb cn | connector:scidb_cn@1.0.0 | |
| concepts[field].local:field:humanities | mapping · scidb cn | connector:scidb_cn@1.0.0 | |
| concepts[field].local:field:life-sciences | mapping · scidb cn | connector:scidb_cn@1.0.0 | |
| concepts[field].local:field:social-science | mapping · scidb cn | connector:scidb_cn@1.0.0 | |
| description | source · scidb cn | connector:scidb_cn@1.0.0 | /metadata/dc/description |
| license_text | source · scidb cn | connector:scidb_cn@1.0.0 | |
| publication_date | source · scidb cn | connector:scidb_cn@1.0.0 | |
| title | source · scidb cn | connector:scidb_cn@1.0.0 | /metadata/dc/title |