@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{ClassenEardleyHempetal.2020, author = {Classen, Alice and Eardley, Connal D. and Hemp, Andreas and Peters, Marcell K. and Peters, Ralph S. and Ssymank, Axel and Steffan-Dewenter, Ingolf}, title = {Specialization of plant-pollinator interactions increases with temperature at Mt. Kilimanjaro}, series = {Ecology and Evolution}, volume = {10}, journal = {Ecology and Evolution}, number = {4}, doi = {10.1002/ece3.6056}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-235959}, pages = {2182-2195}, year = {2020}, abstract = {Aim: Species differ in their degree of specialization when interacting with other species, with significant consequences for the function and robustness of ecosystems. In order to better estimate such consequences, we need to improve our understanding of the spatial patterns and drivers of specialization in interaction networks. Methods: Here, we used the extensive environmental gradient of Mt. Kilimanjaro (Tanzania, East Africa) to study patterns and drivers of specialization, and robustness of plant-pollinator interactions against simulated species extinction with standardized sampling methods. We studied specialization, network robustness and other network indices of 67 quantitative plant-pollinator networks consisting of 268 observational hours and 4,380 plant-pollinator interactions along a 3.4 km elevational gradient. Using path analysis, we tested whether resource availability, pollinator richness, visitation rates, temperature, and/or area explain average specialization in pollinator communities. We further linked pollinator specialization to different pollinator taxa, and species traits, that is, proboscis length, body size, and species elevational ranges. Results: We found that specialization decreased with increasing elevation at different levels of biological organization. Among all variables, mean annual temperature was the best predictor of average specialization in pollinator communities. Specialization differed between pollinator taxa, but was not related to pollinator traits. Network robustness against simulated species extinctions of both plants and pollinators was lowest in the most specialized interaction networks, that is, in the lowlands. Conclusions: Our study uncovers patterns in plant-pollinator specialization along elevational gradients. Mean annual temperature was closely linked to pollinator specialization. Energetic constraints, caused by short activity timeframes in cold highlands, may force ectothermic species to broaden their dietary spectrum. Alternatively or in addition, accelerated evolutionary rates might facilitate the establishment of specialization under warm climates. Despite the mechanisms behind the patterns have yet to be fully resolved, our data suggest that temperature shifts in the course of climate change may destabilize pollination networks by affecting network architecture.}, 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} }