Browsing by Person "Haas-Renninger, Maura"

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Ecosystem services and insect decline: The role of parasitoid Hymenoptera
(2024) Haas-Renninger, Maura; Krogmann, Lars
Parasitoid Hymenoptera provide essential ecosystem services, as they consume their arthropod hosts during their development, controlling host populations and thus contributing to the resilience of ecosystems. However, information on their taxonomic diversity, distribution and population trends are scarce even in well-studied regions such as Central Europe, making it difficult to understand how they are affected by insect decline. Reasons for this knowledge gap are the enormous diversity in contrast to their small size (microhymenoptera), which is why they are referred to as ‘dark taxa’. In recent years, many monitoring projects have been launched to study insect population trends in the context of insect decline and climate change, with a focus on well-studied target groups, such as wild bees, butterflies or beetles. However, parasitoid wasps, which are probably the most species rich group of all insects, are totally neglected although Malaise traps, which are widely used in monitoring studies, catch large numbers of parasitoid Hymenoptera and can therefore serve as a starting point to assess diversity and abundance of this important group. The present work aims to establish a baseline for parasitoid Hymenoptera diversity and abundance in semi-arid meadows in southwestern Germany in a conservational and applied context. It consists of three research papers, each of which contribute to fulfil this goal. The first research paper deals with the efficiency of the fractionator to separate microhymenoptera families from Malaise trap samples and discusses its potential for long-term monitoring studies. The fractionator is an affordable and user-friendly apparatus based on a plastic tub with a sieve that is placed on an orbital shaker. When the complete sample is poured in, it can be separated by shaking into two size fractions. In this study it was used to separate microhymenoptera families from a Malaise trap sample. The results show that 24 out of 34 Hymenoptera families (71 %) were separated into one of the two size fractions, which proves that the fractionator can be a helpful tool to make microhymenoptera from bulk samples accessible for further taxonomic work. In the second research paper, Malaise trap samples from an ongoing insect monitoring program were used to study the relationship of total insect biomass to abundance and diversity of microhymenoptera, as well as to assess the phenology of microhymenoptera families. Microhymenoptera abundance and diversity were positively correlated with total insect biomass, suggesting that insect biomass can be a valuable proxy for abundance trends even for small-sized insects such as microhymenoptera. Further, 90,452 specimens from 26 families belonging to 10 superfamilies of Hymenoptera were counted in total. Microhymenoptera showed two main activity periods during the year, reaching a first peak between June and July and a second between July and August. We could not find any evidence for a negative impact of mowing or grazing on the abundance of microhymenoptera. The families showed different phenological patterns, with varying numbers of activity peaks, and with some families being abundant very early (e.g. Platygastridae) or very late in the season (e.g. Figitidae, Trichogrammatidae). This is the first baseline for microhymenoptera occurrence patterns in Central Europe. The third research paper assesses the effect of mowing on microhymenoptera and how this effect can be reduced through arthropod-friendly mowing techniques, such as an adapted mowing head and a flushing bar. The results show that mowing with a conventional mulching mower has a detrimental effect on microhymenoptera with a loss of up to 64 % of individuals. The adapted mowing head had an effect only on Chalcidoidea, sparing 38 % of individuals compared to the conventional mower. The flushing bar had only a limited positive impact, because it showed a significant effect on total number of microhymenoptera with a significant reduction of 30 % on Chalcidoidea and a tendency for Ichneumonoidea with a reduction of 47 %. This shows that the conventional mowing head can have serious effects on microhymenoptera and that the effect can only be partially mitigated by insect-friendly mowing techniques. I presented the benefits and the limitations of implementing the fractionator in a monitoring workflow. As a positive example, using the fractionator enabled me to create the dataset of research paper 2, which together with research paper 3 can be a valuable reference for adapting schedules for plant protection measures and mowing dates. Insect biomass is strongly correlated with microhymenoptera abundance (research paper 2), which implies that microhymenoptera follow similar negative trends as other insects, but more meadows would need to be included to support our findings. I sorted microhymenoptera from Malaise trap samples as well as suction samples, resulting in different dominating families. Therefore a variety of collecting methods are necessary to assess the whole diversity of parasitoid Hymenoptera. All 103,312 specimens that I processed during my doctoral work are assessed in a digital database, and available for further morphological and molecular work. By linking an insect monitoring initiative with the taxonomically focused GBOLIII: Dark Taxa project, I was able to bring together the best of two worlds, and these combined efforts supported the discovery of a new wasp species. In conclusion, this work lays the foundation for the long-term assessment of parasitoid Hymenoptera in meadow ecosystems and thus contributes to a better understanding of how they are affected by insect decline. It highlights the ecological importance of parasitoid Hymenoptera and serves as a resource for their conservation. In the future, focus must be laid on studying the complex species interaction networks of parasitoid Hymenoptera and associated species. Automated systems such as the DiversityScanner using AI in combination with molecular techniques can help to gain knowledge on this highly important insect group.