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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.
Land use is a key control of insect communities. Here the authors investigate relationships of insect biomass and richness with land use along a climate gradient, finding evidence of urbanisation and agriculture as drivers of decline, and of biomass and species richness not being suitable as mutual surrogates.
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1 Julius-Maximilians-University Würzburg, Field Station Fabrikschleichach, Department of Animal Ecology and Tropical Biology, Würzburg, Germany (GRID:grid.8379.5) (ISNI:0000 0001 1958 8658)
2 Julius-Maximilians-University Würzburg, Department of Animal Ecology and Tropical Biology, Würzburg, Germany (GRID:grid.8379.5) (ISNI:0000 0001 1958 8658)
3 University Zürich, Epidemiology, Biostatistics and Prevention Institute, Zürich, Switzerland (GRID:grid.7400.3) (ISNI:0000 0004 1937 0650)
4 Weihenstephan-Triesdorf University of Applied Sciences, Institute of Ecology and Landscape, Freising, Germany (GRID:grid.4819.4) (ISNI:0000 0001 0704 7467)
5 Weihenstephan-Triesdorf University of Applied Sciences, Botany & Vegetation Science, Faculty of Forestry, Freising, Germany (GRID:grid.4819.4) (ISNI:0000 0001 0704 7467)
6 Technical University of Munich, Ecosystem Dynamics and Forest management Group, Freising, Germany (GRID:grid.6936.a) (ISNI:0000000123222966); Berchtesgaden National Park, Berchtesgaden, Germany (GRID:grid.6936.a)
7 AIM – Advanced Identification Methods GmbH, Leipzig, Germany (GRID:grid.8379.5)
8 Technical University of Munich, TUM School of Life Sciences, Ecoclimatology, Freising, Germany (GRID:grid.6936.a) (ISNI:0000000123222966)
9 University of Bayreuth, Professorship of Ecological Services, Bayreuth Centre of Ecology and Environmental Research (BayCEER), Bayreuth, Germany (GRID:grid.7384.8) (ISNI:0000 0004 0467 6972)
10 Technical University of Munich, Chair of Restoration Ecology, Freising, Germany (GRID:grid.6936.a) (ISNI:0000000123222966)
11 University of Augsburg, Institute of Geography, Augsburg, Germany (GRID:grid.7307.3) (ISNI:0000 0001 2108 9006)
12 SNSB-Zoologische Staatssammlung Muenchen, Munich, Germany (GRID:grid.452781.d) (ISNI:0000 0001 2203 6205)
13 Julius-Maximilians-University Würzburg, Field Station Fabrikschleichach, Department of Animal Ecology and Tropical Biology, Würzburg, Germany (GRID:grid.8379.5) (ISNI:0000 0001 1958 8658); Bavarian Forest National Park, Grafenau, Germany (GRID:grid.452215.5)