@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{SeiboldHothornGossneretal.2021,
  author    = {Seibold, Sebastian and Hothorn, Torsten and Gossner, Martin M. and Simons, Nadja K. and Bl{\"u}thgen, Nico and M{\"u}ller, J{\"o}rg and Ambarl{\i}, Didem and Ammer, Christian and Bauhus, J{\"u}rgen and Fischer, Markus and Habel, Jan C. and Penone, Caterina and Schall, Peter and Schulze, Ernst-Detlef and Weisser, Wolfgang W.},
  title     = {Insights from regional and short-term biodiversity monitoring datasets are valuable: a reply to Daskalova et al. 2021},
  series = {Insect Conservation and Diversity},
  volume    = {14},
  journal   = {Insect Conservation and Diversity},
  number    = {1},
  doi       = {10.1111/icad.12467},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-228309},
  pages     = {144 -- 148},
  year      = {2021},
  abstract  = {Reports of major losses in insect biodiversity have stimulated an increasing interest in temporal population changes. Existing datasets are often limited to a small number of study sites, few points in time, a narrow range of land-use intensities and only some taxonomic groups, or they lack standardised sampling. While new monitoring programs have been initiated, they still cover rather short time periods. Daskalova et al. 2021 (Insect Conservation and Diversity, 14, 1-18) argue that temporal trends of insect populations derived from short time series are biased towards extreme trends, while their own analysis of an assembly of shorter- and longer-term time series does not support an overall insect decline. With respect to the results of Seibold et al. 2019 (Nature, 574, 671-674) based on a 10-year multi-site time series, they claim that the analysis suffers from not accounting for temporal pseudoreplication. Here, we explain why the criticism of missing statistical rigour in the analysis of Seibold et al. (2019) is not warranted. Models that include 'year' as random effect, as suggested by Daskalova et al. (2021), fail to detect non-linear trends and assume that consecutive years are independent samples which is questionable for insect time-series data. We agree with Daskalova et al. (2021) that the assembly and analysis of larger datasets is urgently needed, but it will take time until such datasets are available. Thus, short-term datasets are highly valuable, should be extended and analysed continually to provide a more detailed understanding of insect population changes under the influence of global change, and to trigger immediate conservation actions.},
  language  = {en}
}