Articles | Volume 23, issue 4
https://doi.org/10.5194/bg-23-1291-2026
https://doi.org/10.5194/bg-23-1291-2026
Research article
 | 
18 Feb 2026
Research article |  | 18 Feb 2026

Evaluating the consistency of forest disturbance datasets in continental USA

Laura Eifler, Franziska Müller, and Ana Bastos

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Cited articles

Allen, C. D., Breshears, D. D., and McDowell, N. G.: On underestimation of global vulnerability to tree mortality and forest die-off from hotter drought in the Anthropocene, Ecosphere, 6, art129, https://doi.org/10.1890/ES15-00203.1, 2015. a, b, c, d
Andresini, G., Appice, A., and Malerba, D.: A Deep Semantic Segmentation Approach to Map Forest Tree Dieback in Sentinel-2 Data, IEEE J. Sel. Top. Appl. Earth Obs., 17, 17075–17086, https://doi.org/10.1109/JSTARS.2024.3460981, 2024. a
Banskota, A., Kayastha, N., Falkowski, M. J., Wulder, M. A., Froese, R. E., and White, J. C.: Forest Monitoring Using Landsat Time Series Data: A Review, Can. J. Remote Sens., 40, 362–384, https://doi.org/10.1080/07038992.2014.987376, 2014. a
Bárta, V., Lukeš, P., and Homolová, L.: Early detection of bark beetle infestation in Norway spruce forests of Central Europe using Sentinel-2, International Journal of Applied Earth Observation and Geoinformation, 100, 102335, https://doi.org/10.1016/j.jag.2021.102335, 2021. a
Bastos, A., Orth, R., Reichstein, M., Ciais, P., Viovy, N., Zaehle, S., Anthoni, P., Arneth, A., Gentine, P., Joetzjer, E., Lienert, S., Loughran, T., McGuire, P. C., O, S., Pongratz, J., and Sitch, S.: Vulnerability of European ecosystems to two compound dry and hot summers in 2018 and 2019, Earth Syst. Dynam., 12, 1015–1035, https://doi.org/10.5194/esd-12-1015-2021, 2021. a
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Short summary
Forests provide ecosystem services and biodiversity, but they are increasingly affected by disturbances. We evaluate five forest disturbance datasets across the Unites States to assess their consistency in space, timing, and disturbance agents. While datasets show good agreement in disturbance timing, spatial overlap and agent attribution differ substantially. This emphasizes the need for enhanced data quality assessment, integration, and accuracy to better understand forest disturbances.
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