@article{HeidrichPinkertBrandletal.2021,
  author    = {Heidrich, Lea and Pinkert, Stefan and Brandl, Roland and B{\"a}ssler, Claus and Hacker, Hermann and Roth, Nicolas and Busse, Annika and M{\"u}ller, J{\"o}rg and Friess, Nicolas},
  title     = {Noctuid and geometrid moth assemblages show divergent elevational gradients in body size and color lightness},
  series = {Ecography},
  volume    = {44},
  journal   = {Ecography},
  number    = {8},
  doi       = {10.1111/ecog.05558},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-256694},
  pages     = {1169-1179},
  year      = {2021},
  abstract  = {Previous macroecological studies have suggested that larger and darker insects are favored in cold environments and that the importance of body size and color for the absorption of solar radiation is not limited to diurnal insects. However, whether these effects hold true for local communities and are consistent across taxonomic groups and sampling years remains unexplored. This study examined the variations in body size and color lightness of the two major families of nocturnal moths, Geometridae and Noctuidae, along an elevational gradient of 700 m in Southern Germany. An assemblage-based analysis was performed using community-weighted means and a fourth-corner analysis to test for variations in color and body size among communities as a function of elevation. This was followed by a species-level analysis to test whether species occurrence and abundance along an elevation gradient were related to these traits, after controlling for host plant availability. In both 2007 and 2016, noctuid moth assemblages became larger and darker with increasing elevation, whereas geometrids showed an opposite trend in terms of color lightness and no clear trend in body size. In single species models, the abundance of geometrids, but not of noctuids, was driven by habitat availability. In turn, the abundance of dark-colored noctuids, but not geometrids increased with elevation. While body size and color lightness affect insect physiology and the ability to cope with harsh conditions, divergent trait-environment relationships between both families underline that findings of coarse-scale studies are not necessarily transferable to finer scales. Local abundance and occurrence of noctuids are shaped by morphological traits, whereas that of geometrids are rather shaped by local habitat availability, which can modify their trait-environment-relationship. We discuss potential explanations such as taxon-specific flight characteristics and the effect of microclimatic conditions.},
  language  = {en}
}
@article{MuellerMitesserSchaeferetal.2023,
  author    = {M{\"u}ller, J{\"o}rg and Mitesser, Oliver and Schaefer, H. Martin and Seibold, Sebastian and Busse, Annika and Kriegel, Peter and Rabl, Dominik and Gelis, Rudy and Arteaga, Alejandro and Freile, Juan and Leite, Gabriel Augusto and de Melo, Tomaz Nascimento and LeBien, Jack and Campos-Cerqueira, Marconi and Bl{\"u}thgen, Nico and Tremlett, Constance J. and B{\"o}ttger, Dennis and Feldhaar, Heike and Grella, Nina and Falcon{\´i}-L{\´o}pez, Ana and Donoso, David A. and Moriniere, Jerome and Buřivalov{\´a}, Zuzana},
  title     = {Soundscapes and deep learning enable tracking biodiversity recovery in tropical forests},
  series = {Nature Communications},
  volume    = {14},
  journal   = {Nature Communications},
  doi       = {10.1038/s41467-023-41693-w},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-358130},
  year      = {2023},
  abstract  = {Tropical forest recovery is fundamental to addressing the intertwined climate and biodiversity loss crises. While regenerating trees sequester carbon relatively quickly, the pace of biodiversity recovery remains contentious. Here, we use bioacoustics and metabarcoding to measure forest recovery post-agriculture in a global biodiversity hotspot in Ecuador. We show that the community composition, and not species richness, of vocalizing vertebrates identified by experts reflects the restoration gradient. Two automated measures - an acoustic index model and a bird community composition derived from an independently developed Convolutional Neural Network - correlated well with restoration (adj-R² = 0.62 and 0.69, respectively). Importantly, both measures reflected composition of non-vocalizing nocturnal insects identified via metabarcoding. We show that such automated monitoring tools, based on new technologies, can effectively monitor the success of forest recovery, using robust and reproducible data.},
  language  = {en}
}