A5021245916- Plant and animal studies
- Plant Parasitism and Resistance
- Ecology and Vegetation Dynamics Studies
- Animal and Plant Science Education
- Agricultural and Rural Development Research
- Insect-Plant Interactions and Control
- Insect behavior and control techniques
- Insect and Pesticide Research
- Power Systems Fault Detection
- Fish Ecology and Management Studies
- Rangeland and Wildlife Management
- Study of Mite Species
- Freshwater macroinvertebrate diversity and ecology
- Plant Reproductive Biology
- Botany, Ecology, and Taxonomy Studies
- Noise Effects and Management
- Aquatic Invertebrate Ecology and Behavior
- Urban Green Space and Health
- Islanding Detection in Power Systems
- Insect and Arachnid Ecology and Behavior
- Invertebrate Taxonomy and Ecology
- Electrical Contact Performance and Analysis
German Centre for Integrative Biodiversity Research
2018-2025
Helmholtz Centre for Environmental Research
2018-2025
Martin Luther University Halle-Wittenberg
2021-2024
Deutsches Zentrum für Luft- und Raumfahrt e. V. (DLR)
2023
Abstract Land use change, by disrupting the co-evolved interactions between plants and their pollinators, could be causing plant reproduction to limited pollen supply. Using a phylogenetically controlled meta-analysis on over 2200 experimental studies more than 1200 wild plants, we ask if land intensification is at global scales. Here report that reliant pollinators in urban settings are similarly pollinator-reliant other landscapes. Plants functionally specialized bee natural managed...
Monitoring plant-pollinator interactions is crucial for understanding the factors influencing these relationships across space and time. Traditional methods in pollination ecology are resource-intensive, while time-lapse photography offers potential non-destructive automated complementary techniques. However, accurate identification of pollinators at finer taxonomic levels (i.e., genus or species) requires high enough image quality. This study assessed feasibility using a smartphone setup to...
Develoment of image recognition AI algorithms for flower-visiting arthropods has the potential to revolutionize way we monitor pollinators. Ecologists need light-weight models that can be deployed in a field setting and classify with high accuracy. We tested performance three deep learning models, YOLOv5nano, YOLOv5small, YOLOv7tiny, at object classification real time on eight groups using open-source data. These contained four orders insects are known perform majority pollination services...
ABSTRACT Motivation Pollinators play a crucial role in maintaining Earth's terrestrial biodiversity. However, rapid human‐induced environmental changes are compromising the long‐term persistence of plant‐pollinator interactions. Unfortunately, we lack robust, generalisable data capturing how communities structured across space and time. Here, present EuPPollNet (European Plant‐Pollinator Networks) database, fully open European‐level database containing harmonised taxonomic on interactions...
Complex socio-economic, political and demographic factors have driven the increased conversion of Europe’s semi-natural grasslands to intensive pastures. This trend is particularly strong in some most biodiverse regions continent, such as Central Eastern Europe. Intensive grazing known decrease species diversity alter composition plant insect communities. Comparatively little known, however, about how influences functional traits related pollination structure plant-pollinator interactions....
Abstract 1. Biodiversity is crucial for human health and well-being. Perceived biodiversity - people’s subjective experience of seems to be particularly relevant mental 2. Using photographs audio recordings forests that varied in levels species richness, we conducted two sorting studies assess how people perceive visual acoustic diversity whether their perceptions align with measured tree bird richness (‘actual diversity’). Per study, 48 participants were asked sort the stimuli according any...
Abstract In the face of global pollinator decline, extensively managed grasslands play an important role in supporting stable communities. However, different types extensive management may promote particular plant species and thus functional traits. As traits flowering (e.g., flower size shape) a habitat help determine identity frequency visitors, they can also influence structures plant−pollinator interaction networks (i.e., pollination networks). The aim this study was to examine how type...
Invasive plants create refuge habitat for predators that results in increased levels of seed predation on native plants. We test the effects a large‐scale removal invasive plant Ammophila arenaria predispersal rate experienced by an endangered coastal dune ecosystem. Restoration resulted large and lasting reduction this system, reducing could be explicit goal future restoration projects. The generalized linear mixed statistical model with BACI (before‐after‐control‐impact) design used here...
The increasing incentives stemming from many international initiatives that target sustainable energy production have led to the global success of small hydropower plants. However, there is a growing debate about actual environmental impact these structures on riverine ecosystems, extent some researchers argue they could proportionally greater than large plants; nevertheless, an empirical evaluation applying long-term true “Before-After-Control-Impact (BACI)” approach has never been...
Mass-flowering crops, such as Oilseed Rape (OSR), provide resources for pollinators and benefit from pollination services. Studies that observe the community of interactions between plants are critical to understanding resource needs pollinators. We observed on OSR wild in adjacent semi-natural areas Sachsen-Anhalt, Germany quantify (1) co-flowering share with OSR, (2) identity functional traits network module (3) act connectors hubs. found four common a high percentage their OSR. these all...
ABSTRACT Monitoring plant-pollinator interactions is crucial for understanding factors that influence these relationships across space and time. While traditional methods in pollination ecology are time-consuming resource-intensive, the growing availability of photographic technology, coupled with advancements artificial intelligence classification, offers potential non-destructive automated techniques. However, it important photographs high enough quality to enable insects be identified at...
Abstract Develoment of image recognition AI algorithms for flower-visiting arthropods has the potential to revolutionize way we monitor pollinators. Ecologists need light-weight models that can be deployed in a field setting and classify with high accuracy. We tested performance three deep learning models, YOLOv5nano, YOLOv5small, YOLOv7tiny, at object classification real time on eight groups using open-source data. These contained four orders insects are known perform majority pollination...