Portrait photo of Katarina Meramo

Katarina Meramo

Postdoctoral researcher, NJ, Insect Ecology Unit
Katarina Meramo is a bat ecologist and postdoctoral researcher focusing on ecological patterns and processes in bat communities. Her work uses bioacoustics and deep learning to study biodiversity change, with the aim of developing tools for science, conservation and ecological monitoring.

Presentation

I am an ecologist with a long-standing interest in bats and their roles in ecosystems. My research background is in ecology, biodiversity research and conservation science, with experience from both boreal and tropical ecosystems. I completed my PhD at the University of Helsinki, where I studied how bat communities respond to land-use change and chronic human disturbance, as well as broader biogeographical patterns in bat distributions across Europe.

At SLU, I work within the LIFEPLAN project, where I focus on automated bioacoustic monitoring of bats. I combine large-scale ecological research with bioacoustics and deep learning, and I am also interested in developing open tools that support biodiversity monitoring.

Research

My research focuses on the ecology, conservation and monitoring of bats, with an emphasis on how environmental change and human disturbance shape bat communities across spatial and temporal scales.

Key research themes include:

  • Bat community ecology and species distributions
  • Responses of bats to land-use change, urbanisation and other anthropogenic pressures
  • Bioacoustic monitoring and automated species identification
  • Biodiversity monitoring and conservation applications

Methodologically, my work combines field-based ecology, bioacoustics and statistical modelling with deep learning approaches for species identification. A central part of my research is the development of open tools that enable large-scale bat monitoring.

Research projects

Open science & tools

I am committed to open science. My work includes the development and use of open-source tools for bioacoustic analysis and automated species identification, with a focus on transparency and accessibility in ecological research and conservation.

I was centrally involved in developing BSG-BATS, an open, scientifically validated deep-learning framework for automated identification of bat vocalizations, including an open-source data annotation portal and classifier designed for large-scale bat monitoring.

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