MSc project: Estimating species abundance using trap data

Published: 17 March 2024

Estimating animal populations is crucial for understanding ecological processes and implementing effective conservation measures. However doing so is not straight-forward, given practical limitations from field measurements such as trap data. This project will tackle this issue, by combining theoretical spatial models with data synthesis from published results, to estimate true species densities. To do this we will combine mathematical analysis, computer simulations, and literature review to identify movement properties of ground arthropods.

Application deadline: 2024-04-15

Estimating animal populations is essential tool for understanding ecological processes and implementing conservation measures effectively. By knowing how many individuals of a species exist within an ecosystem, scientists and conservationists can assess population trends, evaluate habitat suitability, and identify potential threats to biodiversity.

However, estimating animal populations is often a challenging task. Traditional methods, such as using traps or conducting visual surveys, provide valuable data but come with limitations. For example, data collected from traps often yield estimates of "activity-density" which is directly linked to the activity level of the relevant species. Thus this measure may not accurately reflect the total population size, as it can be influenced by various factors such as trap placement, trapping techniques, and the behavior of the target species.

The goal of this project is to combine theoretical work on spatial models of random-walk with a data synthesis based on published results, in order to estimate true species densities. The project will involve simple mathematical analysis together with computer simulations of spatial models. This will be combined with a thorough literature analysis in order to find known movement properties of different animal species (focusing on ground arthropods).

The MSc project will be supervised by Dr. Yuval Zelnik, a researcher at the Department of Ecology at SLU, and Prof. Giulia Vico, the head of the unit for plant ecology in the Department of Ecology at SLU.

The research project has the following goals:

Build a random walk model, which will describe the movement of individual animals. Test the effect of several factors on probability of capture: animal density, animal activity, trap spatial structure/arrangement, trap density.

  1.  Collect information about activity of arthropod groups, focusing on highly observed species in agricultural fields. Use data from published studies, and potentially also from unpublished datasets.
  2. Use the previous two steps to build a general (or if not, case by case) method to transform trap data to densities.
  3. Test results of the modelling framework on one or more existing datasets. Compare these results (i.e. densities) on published estimates of species densities (based on other methods).


This project combines a theoretical approach to ecological processes, together with estimating animal behavior from results of published studies. Therefore the following skills and knowledge would be helpful:

  • Programming skills (e.g. Matlab, Python, R), and using these for simulations.
  • Proficiency in English, especially for reading scientific articles.
  • Basic knowledge of mathematical tools, such as calculus and probability theory.
  • Familiarity with animal behavior and population ecology.


Please send an email to with your CV and cover letter explaining why you are interested in this project, and detailing how your experience and skills fit with it.