Potential of Airborne LiDAR Derived Vegetation Structure for the Prediction of Animal Species Richness at Mount Kilimanjaro

Ziegler, Alice; Meyer, Hanna; Otte, Insa; Peters, Marcell K.; Appelhans, Tim; Behler, Christina; Böhning-Gaese, Katrin; Classen, Alice; Detsch, Florian; Deckert, Jürgen; Eardley, Connal D.; Ferger, Stefan W.; Fischer, Markus; Gebert, Friederike; Haas, Michael; Helbig-Bonitz, Maria; Hemp, Andreas; Hemp, Claudia; Kakengi, Victor; Mayr, Antonia V.; ... (2022). Potential of Airborne LiDAR Derived Vegetation Structure for the Prediction of Animal Species Richness at Mount Kilimanjaro. Remote sensing, 14(3), p. 786. Molecular Diversity Preservation International MDPI 10.3390/rs14030786

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The monitoring of species and functional diversity is of increasing relevance for the development of strategies for the conservation and management of biodiversity. Therefore, reliable estimates of the performance of monitoring techniques across taxa become important. Using a unique dataset, this study investigates the potential of airborne LiDAR-derived variables characterizing vegetation structure as predictors for animal species richness at the southern slopes of Mount Kilimanjaro. To disentangle the structural LiDAR information from co-factors related to elevational vegetation zones, LiDAR-based models were compared to the predictive power of elevation models. 17 taxa and 4 feeding guilds were modeled and the standardized study design allowed for a comparison across the assemblages. Results show that most taxa (14) and feeding guilds (3) can be predicted best by elevation with normalized RMSE values but only for three of those taxa and two of those feeding guilds the difference to other models is significant. Generally, modeling performances between different models vary only slightly for each assemblage. For the remaining, structural information at most showed little additional contribution to the performance. In summary, LiDAR observations can be used for animal species prediction. However, the effort and cost of aerial surveys are not always in proportion with the prediction quality, especially when the species distribution follows zonal patterns, and elevation information yields similar results.

Item Type:

Journal Article (Original Article)

Division/Institute:

08 Faculty of Science > Department of Biology > Institute of Plant Sciences (IPS)
08 Faculty of Science > Department of Biology > Institute of Plant Sciences (IPS) > Plant Ecology

UniBE Contributor:

Fischer, Markus and Rutten, Gemma Gerarda Petronella

Subjects:

500 Science > 580 Plants (Botany)

ISSN:

2072-4292

Publisher:

Molecular Diversity Preservation International MDPI

Language:

English

Submitter:

Peter Alfred von Ballmoos-Haas

Date Deposited:

09 Mar 2022 14:16

Last Modified:

09 Mar 2022 14:16

Publisher DOI:

10.3390/rs14030786

BORIS DOI:

10.48350/165878

URI:

https://boris.unibe.ch/id/eprint/165878

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