Dr. Stefan Pinkert

Research interests

Large-scale functional ecology, evolutionary biology, and conservation prioritization in insects.

My research combines distributional, functional, and phylogenetic data to assess the overall patterns, the hotspots of the biodiversity of insects, and knowledge gaps therein, with the goal of informing about the general mechanisms that underpin the remarkable diversity of insets on our planet, guiding insect conservation and improving forecasts of biological responses to climatic changes. My taxonomic focus are Odonata and diurnal butterflies (Rhopalocera). Given the poor availability of essential biodiversity data for these taxa an integral part of my work is developing approaches that allow to integrate different types of biodiversity data, including country-level distribution data, habitat affinities, occurrence records, phylogenies as well as trait data from literature and museum specimens. In combination these data yields increasingly complete information on the global taxonomic, functional, and phylogenetic diversity of insects providing the baseline for area-based conservation and rigorous ecological studies on hitherto largely neglected taxa.

With several studies I investigated the physiological and evolutionary processes that link color and body size variation with the environmental conditions in which insect species live. The main findings of my previous research show that color darkness (melanization) and body size largely determine the distribution, abundance, and phenology of ectothermic taxa in temperate climates. My research furthermore demonstrated that both traits shape the distribution of evolutionary lineages and diversification patterns in insects.

I am a team member of the three global-scale projects HalfEarth, ButterflyNet and GEODE that are centered on mobilizing, compiling, integrating, and extrapolating biodiversity information for data-poor taxa. My main responsibilities are the mobilization of distributional and functional data from various sources (global databases, field guides, atlases and species descriptions) using image analysis techniques and artificial intelligence-based object recognition as well as automatized workflows of taxonomical harmonization, and spatial cleaning, and validation.

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