Artificial Intelligence for an automated Insect Biodiversity Monitoring (AIforIBM)

• Applicants: Privatdozent Dr. Sebastian Tobias Meyer; Professor Dr.-Ing. Patrick Mäder
• Subject Area: Ecology of Land Use ; Ecology and Biodiversity of Animals and Ecosystems, Organismic Interactions
• Term: since 2023
• Project identifier: Deutsche Forschungsgemeinschaft (DFG) - Project number 512413715

Insects and grasslands are intensively studied ecological models because of their high diversity, sensitivity to environmental forcing, and importance for multiple ecosystem functions and services. Substantial decreases in insect abundances and diversity have been documented in the Biodiversity Exploratories and elsewhere, and land-use intensification has been identified as one of the most important drivers of global species loss. Intensification of grassland management has been documented to reduce the abundance and diversity of arthropods, but effects vary depending on the land-use component and group of arthropods studies. A mechanistic understanding of this variability is hindered by the coarse spatial and temporal resolution of insect monitoring imposed by resource constraints because of the labor intensity of established monitoring methods. Consequently, new methods for insect monitoring are needed to enable the required high-resolution data and to further our understanding of land-use effects on insect communities. Digital monitoring systems based on photographs and AI-enabled image recognition are promising techniques to enable these. The current project aims to monitor flying insects in the grassland plots of the Biodiversity Exploratories at very high temporal resolution. We will use available RGB-camera trap systems and develop deep learning algorithms to quantify insect abundance, morpho-group diversity, and body size distributions. We will be building on the wealth of existing data on insects from the Biodiversity Exploratories for training data and to benchmark the performance of the AI image recognition. Deploying an embedded sensor system with mobile connectivity to monitor insects, we aim to conduct continuous in-situ measurements in the grassland plots of the three regions of the Biodiversity Exploratories before, during, and after different land-management activities. Because of the high temporal resolution of our data, we can investigate how land-use activities affect the dynamics and stability of the insect communities by quantifying the reference state, disturbance effects, and recovery phases directly. We will differentiate between demographic and (re)colonization processes in response to disturbances by land-use, exploiting that demographic and behavioral processes operate at different time scales, for example recolonization being much faster than reproduction, Thereby, this project will advance the technology available for insect monitoring and the mechanistic understanding of the effects of land use on insect communities.

• DFG Programme: Infrastructure Priority Programmes
• Subproject of: SPP 1374: Biodiversity Exploratories