@article{ZieglerMeyerOtteetal.2022,
  author    = {Ziegler, Alice and Meyer, Hanna and Otte, Insa and Peters, Marcell K. and Appelhans, Tim and Behler, Christina and B{\"o}hning-Gaese, Katrin and Classen, Alice and Detsch, Florian and Deckert, J{\"u}rgen and Eardley, Connal D. and Ferger, Stefan W. and Fischer, Markus and Gebert, Friederike and Haas, Michael and Helbig-Bonitz, Maria and Hemp, Andreas and Hemp, Claudia and Kakengi, Victor and Mayr, Antonia V. and Ngereza, Christine and Reudenbach, Christoph and R{\"o}der, Juliane and Rutten, Gemma and Schellenberger Costa, David and Schleuning, Matthias and Ssymank, Axel and Steffan-Dewenter, Ingolf and Tardanico, Joseph and Tschapka, Marco and Vollst{\"a}dt, Maximilian G. R. and W{\"o}llauer, Stephan and Zhang, Jie and Brandl, Roland and Nauss, Thomas},
  title     = {Potential of airborne LiDAR derived vegetation structure for the prediction of animal species richness at Mount Kilimanjaro},
  series = {Remote Sensing},
  volume    = {14},
  journal   = {Remote Sensing},
  number    = {3},
  issn      = {2072-4292},
  doi       = {10.3390/rs14030786},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-262251},
  year      = {2022},
  abstract  = {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.},
  language  = {en}
}
@article{BaeHeidrichLevicketal.2020,
  author    = {Bae, Soyeon and Heidrich, Lea and Levick, Shaun R. and Gossner, Martin M. and Seibold, Sebastian and Weisser, Wolfgang W. and Magdon, Paul and Serebryanyk, Alla and B{\"a}ssler, Claus and Sch{\"a}fer, Deborah and Schulze, Ernst-Detlef and Doerfler, Inken and M{\"u}ller, J{\"o}rg and Jung, Kirsten and Heurich, Marco and Fischer, Markus and Roth, Nicolas and Schall, Peter and Boch, Steffen and W{\"o}llauer, Stephan and Renner, Swen C. and M{\"u}ller, J{\"o}rg},
  title     = {Dispersal ability, trophic position and body size mediate species turnover processes: Insights from a multi-taxa and multi-scale approach},
  series = {Diversity and Distribution},
  volume    = {27},
  journal   = {Diversity and Distribution},
  number    = {3},
  doi       = {10.1111/ddi.13204},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-236117},
  pages     = {439-453},
  year      = {2020},
  abstract  = {Aim: Despite increasing interest in β-diversity, that is the spatial and temporal turnover of species, the mechanisms underlying species turnover at different spatial scales are not fully understood, although they likely differ among different functional groups. We investigated the relative importance of dispersal limitations and the environmental filtering caused by vegetation for local, multi-taxa forest communities differing in their dispersal ability, trophic position and body size. Location: Temperate forests in five regions across Germany. Methods: In the inter-region analysis, the independent and shared effects of the regional spatial structure (regional species pool), landscape spatial structure (dispersal limitation) and environmental factors on species turnover were quantified with a 1-ha grain across 11 functional groups in up to 495 plots by variation partitioning. In the intra-region analysis, the relative importance of three environmental factors related to vegetation (herb and tree layer composition and forest physiognomy) and spatial structure for species turnover was determined. Results: In the inter-region analysis, over half of the explained variation in community composition (23\% of the total explained 35\%) was explained by the shared effects of several factors, indicative of spatially structured environmental filtering. Among the independent effects, environmental factors were the strongest on average over 11 groups, but the importance of landscape spatial structure increased for less dispersive functional groups. In the intra-region analysis, the independent effect of plant species composition had a stronger influence on species turnover than forest physiognomy, but the relative importance of the latter increased with increasing trophic position and body size. Main conclusions: Our study revealed that the mechanisms structuring assemblage composition are associated with the traits of functional groups. Hence, conservation frameworks targeting biodiversity of multiple groups should cover both environmental and biogeographical gradients. Within regions, forest management can enhance β-diversity particularly by diversifying tree species composition and forest physiognomy.},
  language  = {en}
}