TY - JOUR A1 - Ziegler, Alice A1 - Meyer, Hanna A1 - Otte, Insa A1 - Peters, Marcell K. A1 - Appelhans, Tim A1 - Behler, Christina A1 - Böhning-Gaese, Katrin A1 - Classen, Alice A1 - Detsch, Florian A1 - Deckert, Jürgen A1 - Eardley, Connal D. A1 - Ferger, Stefan W. A1 - Fischer, Markus A1 - Gebert, Friederike A1 - Haas, Michael A1 - Helbig-Bonitz, Maria A1 - Hemp, Andreas A1 - Hemp, Claudia A1 - Kakengi, Victor A1 - Mayr, Antonia V. A1 - Ngereza, Christine A1 - Reudenbach, Christoph A1 - Röder, Juliane A1 - Rutten, Gemma A1 - Schellenberger Costa, David A1 - Schleuning, Matthias A1 - Ssymank, Axel A1 - Steffan-Dewenter, Ingolf A1 - Tardanico, Joseph A1 - Tschapka, Marco A1 - Vollstädt, Maximilian G. R. A1 - Wöllauer, Stephan A1 - Zhang, Jie A1 - Brandl, Roland A1 - Nauss, Thomas T1 - Potential of airborne LiDAR derived vegetation structure for the prediction of animal species richness at Mount Kilimanjaro JF - Remote Sensing N2 - 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. KW - biodiversity KW - species richness KW - LiDAR KW - elevation KW - partial least square regression KW - arthropods KW - birds KW - bats KW - predictive modeling Y1 - 2022 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-262251 SN - 2072-4292 VL - 14 IS - 3 ER - TY - JOUR A1 - Dorji, Yonten A1 - Schuldt, Bernhard A1 - Neudam, Liane A1 - Dorji, Rinzin A1 - Middleby, Kali A1 - Isasa, Emilie A1 - Körber, Klaus A1 - Ammer, Christian A1 - Annighöfer, Peter A1 - Seidel, Dominik T1 - Three-dimensional quantification of tree architecture from mobile laser scanning and geometry analysis JF - Trees N2 - Key message Mobile laser scanning and geometrical analysis revealed relationships between tree geometry and seed dispersal mechanism, latitude of origin, as well as growth. Abstract The structure and dynamics of a forest are defined by the architecture and growth patterns of its individual trees. In turn, tree architecture and growth result from the interplay between the genetic building plans and environmental factors. We set out to investigate whether (1) latitudinal adaptations of the crown shape occur due to characteristic solar elevation angles at a species’ origin, (2) architectural differences in trees are related to seed dispersal strategies, and (3) tree architecture relates to tree growth performance. We used mobile laser scanning (MLS) to scan 473 trees and generated three-dimensional data of each tree. Tree architectural complexity was then characterized by fractal analysis using the box-dimension approach along with a topological measure of the top heaviness of a tree. The tree species studied originated from various latitudinal ranges, but were grown in the same environmental settings in the arboretum. We found that trees originating from higher latitudes had significantly less top-heavy geometries than those from lower latitudes. Therefore, to a certain degree, the crown shape of tree species seems to be determined by their original habitat. We also found that tree species with wind-dispersed seeds had a higher structural complexity than those with animal-dispersed seeds (p < 0.001). Furthermore, tree architectural complexity was positively related to the growth performance of the trees (p < 0.001). We conclude that the use of 3D data from MLS in combination with geometrical analysis, including fractal analysis, is a promising tool to investigate tree architecture. KW - tree architecture KW - LiDAR KW - fractal analysis KW - seed dispersal strategy KW - latitude KW - tree growth Y1 - 2021 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-307501 SN - 0931-1890 SN - 1432-2285 VL - 35 IS - 4 ER - TY - JOUR A1 - Stereńczak, Krzysztof A1 - Laurin, Gaia Vaglio A1 - Chirici, Gherardo A1 - Coomes, David A. A1 - Dalponte, Michele A1 - Latifi, Hooman A1 - Puletti, Nicola T1 - Global Airborne Laser Scanning Data Providers Database (GlobALS) — a new tool for monitoring ecosystems and biodiversity JF - Remote Sensing N2 - Protection and recovery of natural resource and biodiversity requires accurate monitoring at multiple scales. Airborne Laser Scanning (ALS) provides high-resolution imagery that is valuable for monitoring structural changes to vegetation, providing a reliable reference for ecological analyses and comparison purposes, especially if used in conjunction with other remote-sensing and field products. However, the potential of ALS data has not been fully exploited, due to limits in data availability and validation. To bridge this gap, the global network for airborne laser scanner data (GlobALS) has been established as a worldwide network of ALS data providers that aims at linking those interested in research and applications related to natural resources and biodiversity monitoring. The network does not collect data itself but collects metadata and facilitates networking and collaborative research amongst the end-users and data providers. This letter describes this facility, with the aim of broadening participation in GlobALS. KW - LiDAR KW - forest KW - database KW - networking KW - GlobALS Y1 - 2020 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-207819 SN - 2072-4292 VL - 12 IS - 11 ER -