# Can ecological niche models be used to accurately predict the distribution of invasive insects? A case study of <i>Hyphantria cunea</i> in China

*PRI Rank #2 · Topics and Trends in Most Cited Forest Insect Ecology and Management Papers, Class of 2026*

*Canonical URL: https://pri.pepkio.com/top-papers/forest-insect-ecology-and-management/2026/rank-2*

| Field | Value |
| --- | --- |
| Rank | #2 |
| 18m citations | 29 |
| Journal | Ecology and Evolution |
| Year | 2024 |
| DOI | 10.1002/ece3.11159 |
| Corresponding authors | Shouhui Sun, Guanghua Zhao, Xiao Lin |
| Institution | National Forestry and Grassland Administration, China |

**Ranking page:** [Topics and Trends in Most Cited Forest Insect Ecology and Management Papers, Class of 2026](https://pri.pepkio.com/top-papers/forest-insect-ecology-and-management/2026)

**Paper link:** [10.1002/ece3.11159](https://doi.org/10.1002/ece3.11159)

## Topics

species distribution modeling · MaxEnt · Biomod2 · ensemble modeling · Hyphantria cunea · invasive insects · prediction accuracy · species distribution modeling · global data · invasive area data · Future climate scenarios · habitat suitability · species distribution modeling · model validation · species occurrence records · China distribution · short-term prediction · long-term prediction

## Cite this ranking

```
Pepkio Research Index (PRI). Topics and Trends in Most Cited Forest Insect Ecology and Management Papers, Class of 2026. https://pri.pepkio.com/top-papers/forest-insect-ecology-and-management/2026. Accessed 2026-07-31.

Zheng Su, Tinsley Li, Thematic Shifts in Early-High-Impact Cancer Genomics and Diagnostics Research: A Bibliometric and Semantic Analysis. bioRxiv 2026.07.04.736459; doi: https://doi.org/10.64898/2026.07.04.736459
```