Publication Details

Category Text Publication
Reference Category Journals
DOI 10.1016/j.ecolind.2025.114245
Licence creative commons licence
Title (Primary) Drivers of remotely sensed tree height heterogeneity across spatial scales: Tree species diversity effects depend on local conditions and forest type
Author Rahmsdorf, E. ORCID logo ; Doktor, D.; Feilhauer, H.; Brede, B.; Dienstbach, L.; Eisenhauer, N.; Hildebrandt, A.; Rüger, N.; Lange, M.
Source Titel Ecological Indicators
Year 2025
Department CHS; RS
Volume 179
Page From art. 114245
Language englisch
Topic T5 Future Landscapes
Data and Software links https://doi.org/10.25829/NT8Q-YC45
Supplements https://ars.els-cdn.com/content/image/1-s2.0-S1470160X2501177X-mmc1.pdf
Keywords Canopy height models; Temperate forest; Height heterogeneity; LiDAR; Tree species diversity
Abstract Forests with high structural complexity provide a variety of ecosystem functions and services. They are further associated with greater ecosystem stability. Area-wide canopy height models with high spatial resolution are a powerful tool for deriving forest structural attributes. However, the drivers of forest structural heterogeneity as captured by canopy height models, such as tree height heterogeneity, are not fully understood across spatial scales. Here, we analyzed the relationship of tree species diversity and tree height heterogeneity (1) in a tree diversity experiment, (2) among three forest inventory sites across Germany and (3) on the German national scale. We show that the effect of tree species diversity on tree height heterogeneity depends on the spatial scale and local conditions. Depending on canopy height model resolution, effects of topography, tree species composition and data acquisition parameters of canopy height models have a larger influence on tree height heterogeneity compared to tree species diversity. Moreover, canopy cover fraction is highly correlated with height heterogeneity. By combining our findings from different inventory sites and examining national patterns, this study provides new insights for the application and interpretation of remotely sensed forest biodiversity indicators.
Persistent UFZ Identifier https://www.ufz.de/index.php?en=20939&ufzPublicationIdentifier=31437
Rahmsdorf, E., Doktor, D., Feilhauer, H., Brede, B., Dienstbach, L., Eisenhauer, N., Hildebrandt, A., Rüger, N., Lange, M. (2025):
Drivers of remotely sensed tree height heterogeneity across spatial scales: Tree species diversity effects depend on local conditions and forest type
Ecol. Indic. 179 , art. 114245 10.1016/j.ecolind.2025.114245