@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{SchleuningFarwigPetersetal.2011, author = {Schleuning, Matthias and Farwig, Nina and Peters, Marcell K. and Bergsdorf, Thomas and Bleher, B{\"a}rbel and Brandl, Roland and Dalitz, Helmut and Fischer, Georg and Freund, Wolfram and Gikungu, Mary W. and Hagen, Melanie and Garcia, Francisco Hita and Kagezi, Godfrey H. and Kaib, Manfred and Kraemer, Manfred and Lung, Tobias and Naumann, Clas M. and Schaab, Gertrud and Templin, Mathias and Uster, Dana and W{\"a}gele, J. Wolfgang and B{\"o}hning-Gaese, Katrin}, title = {Forest Fragmentation and Selective Logging Have Inconsistent Effects on Multiple Animal-Mediated Ecosystem Processes in a Tropical Forest}, series = {PLoS ONE}, volume = {6}, journal = {PLoS ONE}, number = {11}, doi = {10.1371/journal.pone.0027785}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-140093}, pages = {e27785}, year = {2011}, abstract = {Forest fragmentation and selective logging are two main drivers of global environmental change and modify biodiversity and environmental conditions in many tropical forests. The consequences of these changes for the functioning of tropical forest ecosystems have rarely been explored in a comprehensive approach. In a Kenyan rainforest, we studied six animal-mediated ecosystem processes and recorded species richness and community composition of all animal taxa involved in these processes. We used linear models and a formal meta-analysis to test whether forest fragmentation and selective logging affected ecosystem processes and biodiversity and used structural equation models to disentangle direct from biodiversity-related indirect effects of human disturbance on multiple ecosystem processes. Fragmentation increased decomposition and reduced antbird predation, while selective logging consistently increased pollination, seed dispersal and army-ant raiding. Fragmentation modified species richness or community composition of five taxa, whereas selective logging did not affect any component of biodiversity. Changes in the abundance of functionally important species were related to lower predation by antbirds and higher decomposition rates in small forest fragments. The positive effects of selective logging on bee pollination, bird seed dispersal and army-ant raiding were direct, i.e. not related to changes in biodiversity, and were probably due to behavioural changes of these highly mobile animal taxa. We conclude that animal-mediated ecosystem processes respond in distinct ways to different types of human disturbance in Kakamega Forest. Our findings suggest that forest fragmentation affects ecosystem processes indirectly by changes in biodiversity, whereas selective logging influences processes directly by modifying local environmental conditions and resource distributions. The positive to neutral effects of selective logging on ecosystem processes show that the functionality of tropical forests can be maintained in moderately disturbed forest fragments. Conservation concepts for tropical forests should thus include not only remaining pristine forests but also functionally viable forest remnants.}, language = {en} } @article{PetersHempAppelhansetal.2016, author = {Peters, Marcell K. and Hemp, Andreas and Appelhans, Tim and Behler, Christina and Classen, Alice and Detsch, Florian and Ensslin, Andreas and Ferger, Stefan W. and Frederiksen, Sara B. and Gebert, Frederike and Haas, Michael and Helbig-Bonitz, Maria and Hemp, Claudia and Kindeketa, William J. and Mwangomo, Ephraim and Ngereza, Christine and Otte, Insa and R{\"o}der, Juliane and Rutten, Gemma and Costa, David Schellenberger and Tardanico, Joseph and Zancolli, Giulia and Deckert, J{\"u}rgen and Eardley, Connal D. and Peters, Ralph S. and R{\"o}del, Mark-Oliver and Schleuning, Matthias and Ssymank, Axel and Kakengi, Victor and Zhang, Jie and B{\"o}hning-Gaese, Katrin and Brandl, Roland and Kalko, Elisabeth K.V. and Kleyer, Michael and Nauss, Thomas and Tschapka, Marco and Fischer, Markus and Steffan-Dewenter, Ingolf}, title = {Predictors of elevational biodiversity gradients change from single taxa to the multi-taxa community level}, series = {Nature Communications}, volume = {7}, journal = {Nature Communications}, doi = {10.1038/ncomms13736}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-169374}, year = {2016}, abstract = {The factors determining gradients of biodiversity are a fundamental yet unresolved topic in ecology. While diversity gradients have been analysed for numerous single taxa, progress towards general explanatory models has been hampered by limitations in the phylogenetic coverage of past studies. By parallel sampling of 25 major plant and animal taxa along a 3.7 km elevational gradient on Mt. Kilimanjaro, we quantify cross-taxon consensus in diversity gradients and evaluate predictors of diversity from single taxa to a multi-taxa community level. While single taxa show complex distribution patterns and respond to different environmental factors, scaling up diversity to the community level leads to an unambiguous support for temperature as the main predictor of species richness in both plants and animals. Our findings illuminate the influence of taxonomic coverage for models of diversity gradients and point to the importance of temperature for diversification and species coexistence in plant and animal communities.}, language = {en} }