@article{RequierPailletLarocheetal.2019,
  author    = {Requier, Fabrice and Paillet, Yoan and Laroche, Fabienne and Rutschmann, Benjamin and Zhang, Jie and Lombardi, Fabio and Svoboda, Miroslav and Steffan-Dewenter, Ingolf},
  title     = {Contribution of European forests to safeguard wild honeybee populations},
  series = {Conservation Letters},
  volume    = {13},
  journal   = {Conservation Letters},
  number    = {2},
  doi       = {10.1111/conl.12693},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-204407},
  pages     = {e12693},
  year      = {2019},
  abstract  = {Abstract Recent studies reveal the use of tree cavities by wild honeybee colonies in European forests. This highlights the conservation potential of forests for a highly threatened component of the native entomofauna in Europe, but currently no estimate of potential wild honeybee population sizes exists. Here, we analyzed the tree cavity densities of 106 forest areas across Europe and inferred an expected population size of wild honeybees. Both forest and management types affected the density of tree cavities. Accordingly, we estimated that more than 80,000 wild honeybee colonies could be sustained in European forests. As expected, potential conservation hotspots were identified in unmanaged forests, and, surprisingly, also in other large forest areas across Europe. Our results contribute to the EU policy strategy to halt pollinator declines and reveal the potential of forest areas for the conservation of so far neglected wild honeybee populations in Europe.},
  language  = {en}
}
@article{UhlerRedlichZhangetal.2021,
  author    = {Uhler, Johannes and Redlich, Sarah and Zhang, Jie and Hothorn, Torsten and Tobisch, Cynthia and Ewald, J{\"o}rg and Thorn, Simon and Seibold, Sebastian and Mitesser, Oliver and Morin{\`e}re, J{\´e}r{\^o}me and Bozicevic, Vedran and Benjamin, Caryl S. and Englmeier, Jana and Fricke, Ute and Ganuza, Cristina and Haensel, Maria and Riebl, Rebekka and Rojas-Botero, Sandra and Rummler, Thomas and Uphus, Lars and Schmidt, Stefan and Steffan-Dewenter, Ingolf and M{\"u}ller, J{\"o}rg},
  title     = {Relationships of insect biomass and richness with land use along a climate gradient},
  series = {Nature Communications},
  volume    = {12},
  journal   = {Nature Communications},
  number    = {1},
  doi       = {10.1038/s41467-021-26181-3},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-265058},
  year      = {2021},
  abstract  = {Recently reported insect declines have raised both political and social concern. Although the declines have been attributed to land use and climate change, supporting evidence suffers from low taxonomic resolution, short time series, a focus on local scales, and the collinearity of the identified drivers. In this study, we conducted a systematic assessment of insect populations in southern Germany, which showed that differences in insect biomass and richness are highly context dependent. We found the largest difference in biomass between semi-natural and urban environments (-42\%), whereas differences in total richness (-29\%) and the richness of threatened species (-56\%) were largest from semi-natural to agricultural environments. These results point to urbanization and agriculture as major drivers of decline. We also found that richness and biomass increase monotonously with increasing temperature, independent of habitat. The contrasting patterns of insect biomass and richness question the use of these indicators as mutual surrogates. Our study provides support for the implementation of more comprehensive measures aimed at habitat restoration in order to halt insect declines.},
  language  = {en}
}
@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}
}