Making the most out of synoptic sampling campaigns and large datasets: development of new statistical tools to optimize evaluation of environmental change (UNSUM)

Last changed: 28 August 2023
The figur shows a map of Sweden with the temporal trends in log-transformed and mean-centered total organic carbon contrations in Swedish lakes from 2008 to 2021. The highest values are shown in red, and are located in the south of the country.

In this project, we will develop new statistical methodology to analyze trends in data from the Swedish Lake Survey to identify ongoing changes in brownification and oligotrophication and connect them to an extensive list of potential drivers.


Sweden has extensive, long-term and high quality monitoring programs to monitor the state of the environment. These programs have been ongoing for decades and produce large amounts of data that are publicly available in online databases. Unfortunately, the development of appropriate statistical methods has not received the same focus and many of the scientific evaluations of temporal trends in data rely on statistical trend methods that are 40 years old and developed for single sites and short monitoring periods, resulting in a substantial loss of information carried by monitoring.


The main focus of this project is to

  • develop standardized and sound practices to evaluate spatially varying trends in monitoring programs with high spatial and low temporal resolution, using the Swedish Lake Survey as basis. 
  • use these methods to identify regionally differentiated trends of brownification and oligotrophication of Swedish lakes and
  •  to discriminate between large-scale and local scale drivers of brownification and oligotrophication.


von Brömssen et. al., 2023. Temporal trend evaluation in monitoring programs with high spatial resolution and low temporal resolution using geographically weighted regression models


Participating researchers:

Claudia von Brömssen (project leader, SLU), Karin Eklöf (SLU), Brian Huser (SLU)


This study is funded by Formas Grant No. 2022–00942


Claudia von Brömssen Senior Lecturer at the Department of Energy and Technology; Applied statistics and mathematics

Telephone: 018-671720