TY - JOUR A1 - Bartomeus, Ignasi A1 - Potts, Simon G. A1 - Steffan-Dewenter, Ingolf A1 - Vaissiere, Bernard E. A1 - Woyciechowski, Michal A1 - Krewenka, Kristin M. A1 - Tscheulin, Thomas A1 - Roberts, Stuart P. M. A1 - Szentgyoergyi, Hajnalka A1 - Westphal, Catrin A1 - Bommarco, Riccardo T1 - Contribution of insect pollinators to crop yield and quality varies with agricultural intensification JF - PEERJ N2 - Background. Up to 75% of crop species benefit at least to some degree from animal pollination for fruit or seed set and yield. However, basic information on the level of pollinator dependence and pollinator contribution to yield is lacking for many crops. Even less is known about how insect pollination affects crop quality. Given that habitat loss and agricultural intensification are known to decrease pollinator richness and abundance, there is a need to assess the consequences for different components of crop production. Methods. We used pollination exclusion on flowers or inflorescences on a whole plant basis to assess the contribution of insect pollination to crop yield and quality in four flowering crops (spring oilseed rape, field bean, strawberry, and buckwheat) located in four regions of Europe. For each crop, we recorded abundance and species richness of flower visiting insects in ten fields located along a gradient from simple to heterogeneous landscapes. Results. Insect pollination enhanced average crop yield between 18 and 71% depending on the crop. Yield quality was also enhanced in most crops. For instance, oilseed rape had higher oil and lower chlorophyll contents when adequately pollinated, the proportion of empty seeds decreased in buckwheat, and strawberries' commercial grade improved; however, we did not find higher nitrogen content in open pollinated field beans. Complex landscapes had a higher overall species richness of wild pollinators across crops, but visitation rates were only higher in complex landscapes for some crops. On the contrary, the overall yield was consistently enhanced by higher visitation rates, but not by higher pollinator richness. Discussion. For the four crops in this study, there is clear benefit delivered by pollinators on yield quantity and/or quality, but it is not maximized under current agricultural intensification. Honeybees, the most abundant pollinator, might partially compensate the loss of wild pollinators in some areas, but our results suggest the need of landscape-scale actions to enhance wild pollinator populations. KW - biodiversity KW - pollination KW - honeybee KW - wild bees KW - agroecosystems KW - native pollinators KW - species richness KW - bee pollinators KW - wild KW - ecosystemservices KW - fruit-quality KW - oilseed rape KW - land-use KW - honey KW - patterns Y1 - 2014 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-116928 SN - 2167-9843 VL - 2 IS - e328 ER - TY - JOUR A1 - Mayr, Antonia V. A1 - Peters, Marcell K. A1 - Eardley, Connal D. A1 - Renner, Marion E. A1 - Röder, Juliane A1 - Steffan-Dewenter, Ingolf T1 - Climate and food resources shape species richness and trophic interactions of cavity-nesting Hymenoptera JF - Journal of Biogeography N2 - Aim: Temperature, food resources and top‐down regulation by antagonists are considered as major drivers of insect diversity, but their relative importance is poorly understood. Here, we used cavity‐nesting communities of bees, wasps and their antagonists to reveal the role of temperature, food resources, parasitism rate and land use as drivers of species richness at different trophic levels along a broad elevational gradient. Location: Mt. Kilimanjaro, Tanzania. Taxon: Cavity‐nesting Hymenoptera (Hymenoptera: Apidae, Colletidae, Megachilidae, Crabronidae, Sphecidae, Pompilidae, Vespidae). Methods: We established trap nests on 25 study sites that were distributed over similar large distances in terms of elevation along an elevational gradient from 866 to 1788 m a.s.l., including both natural and disturbed habitats. We quantified species richness and abundance of bees, wasps and antagonists, parasitism rates and flower or arthropod food resources. Data were analysed with generalized linear models within a multi‐model inference framework. Results: Elevational species richness patterns changed with trophic level from monotonically declining richness of bees to increasingly humped‐shaped patterns for caterpillar‐hunting wasps, spider‐hunting wasps and antagonists. Parasitism rates generally declined with elevation but were higher for wasps than for bees. Temperature was the most important predictor of both bee and wasp host richness patterns. Antagonist richness patterns were also well predicted by temperature, but in contrast to host richness patterns, additionally by resource abundance and diversity. The conversion of natural habitats through anthropogenic land use, which included biomass removal, agricultural inputs, vegetation structure and percentage of surrounding agricultural habitats, had no significant effects on bee and wasp communities. Main conclusions: Our study underpins the importance of temperature as a main driver of diversity gradients in ectothermic organisms and reveals the increasingly important role of food resources at higher trophic levels. Higher parasitism rates at higher trophic levels and at higher temperatures indicated that the relative importance of bottom‐up and top‐down drivers of species richness change across trophic levels and may respond differently to future climate change. KW - land-use change KW - species richness KW - trophic levels KW - wasps KW - feeding guilds KW - antagonists KW - bees KW - bottom‐up and top‐down control KW - elevational gradients Y1 - 2020 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-208101 VL - 47 IS - 4 ER - TY - JOUR A1 - Ziegler, Alice A1 - Meyer, Hanna A1 - Otte, Insa A1 - Peters, Marcell K. A1 - Appelhans, Tim A1 - Behler, Christina A1 - Böhning-Gaese, Katrin A1 - Classen, Alice A1 - Detsch, Florian A1 - Deckert, Jürgen A1 - Eardley, Connal D. A1 - Ferger, Stefan W. A1 - Fischer, Markus A1 - Gebert, Friederike A1 - Haas, Michael A1 - Helbig-Bonitz, Maria A1 - Hemp, Andreas A1 - Hemp, Claudia A1 - Kakengi, Victor A1 - Mayr, Antonia V. A1 - Ngereza, Christine A1 - Reudenbach, Christoph A1 - Röder, Juliane A1 - Rutten, Gemma A1 - Schellenberger Costa, David A1 - Schleuning, Matthias A1 - Ssymank, Axel A1 - Steffan-Dewenter, Ingolf A1 - Tardanico, Joseph A1 - Tschapka, Marco A1 - Vollstädt, Maximilian G. R. A1 - Wöllauer, Stephan A1 - Zhang, Jie A1 - Brandl, Roland A1 - Nauss, Thomas T1 - Potential of airborne LiDAR derived vegetation structure for the prediction of animal species richness at Mount Kilimanjaro JF - Remote Sensing N2 - 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. KW - biodiversity KW - species richness KW - LiDAR KW - elevation KW - partial least square regression KW - arthropods KW - birds KW - bats KW - predictive modeling Y1 - 2022 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-262251 SN - 2072-4292 VL - 14 IS - 3 ER -