Data · dataset · 2026
Effects of landscape pattern on the damage of pine wilt disease in the head region of the Three Gorges Reservior
Listed in ScienceDB
The spread of pine wilt disease (PWD) within affected areas is related to the spatial heterogeneity of the landscape.
Description
Investigating the effects of landscape patterns on PWD severity can facilitate the construction of landscape ecological security patterns and further contribute to long-term regional prevention and control strategies. Based on unmanned aerial vehicle (UAV) remote sensing data and forest resource inventory data, we adopted correlation analysis method and hierarchical segmentation in the linear mixed-effects model to evaluate the impact of landscape patterns on PWD at both the landscape and patch levels in the head region of the Three Gorges Reservoir.
The results indicated that at the landscape level, larger patch sizes and higher landscape fragmentation were associated with lower PWD severity in the region. Area characteristics and aggregation explained 45.9% and 29.3% of the variation in disease density, respectively. At the patch level, the fragmentation of pure pine forest (host) patches was significantly positively correlated with disease density, while more regular patch shapes were associated with greater PWD severity.
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The area and connectivity of native dominant forest (non-host) patches were also significantly positively correlated with disease density. The aggregation and connectivity of farmland and water (non-host) patches were significantly negatively correlated with the disease density. Therefore, fine-scale patch classification and integrated consideration of the landscape ecological processes in different patches would be crucial for accurately understanding the occurrence and spread of the epidemic.
Links
Where it is published
- DOI doi.org/10.57760/sciencedb.cjae.00126 ↗
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 · Medicine & Health · Social Science
- Inferred from text
- Disease 75% · Ecological applications 72% · Satellite remote sensing 65%
Provenance · 1 source records, 13 field assertions
| Source | Key | Last seen | Raw |
|---|---|---|---|
| ScienceDB | 10.57760/sciencedb.cjae.00126 | 11 d ago | JSON v1 |
| Field | Assertion | Extractor | Evidence |
|---|---|---|---|
| concepts[disease].local:disease:disease | enrichment · scidb cn | keyword-concept-rules@1.0.0 | title+description (75%) |
| concepts[field].anzsrc:group:4102 | enrichment · scidb cn | taxonomy-embedding@1.0.0 | title+keywords+description (72%) |
| 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:medicine-health | mapping · scidb cn | connector:scidb_cn@1.0.0 | |
| concepts[field].local:field:social-science | mapping · scidb cn | connector:scidb_cn@1.0.0 | |
| concepts[modality].local:modality:remote-sensing | enrichment · scidb cn | keyword-concept-rules@1.0.0 | title+description (65%) |
| 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 |