Statistical study design for cost-effective biodiversity monitoring

Datharsis, a University of Granada spin-off specialised in explainable data analysis, is looking to join a consortium as the partner responsible for study design and data analysis, either leading a work package or contributing specific tasks.

Much of the cost of biodiversity monitoring comes from the number of sites, visits and samples processed. Using our own computational methods, we determine how many samples are needed, and where and when to take them, to answer the policy question with enough statistical power. That means lower costs without losing reliability.

What we offer:

• Statistical design of monitoring schemes: factors, sampling strategy and sample size

• Design of monitoring schemes for the early detection of invasive alien species

• Integration of multi-site, multi-season and omics-based data into interpretable indicators

• Models that separate shared trends from site-specific variability, as our team has done for warming trends across high mountain lakes

• Reproducible analysis pipelines that monitoring bodies can reuse

• Access to DathaSuite, so monitoring teams can run the same analyses on new data

• Training for monitoring staff and researchers in study design and interpretable analysis, so the methods stay in use after the project ends

We are looking for consortia with monitoring networks, environmental agencies or ecology groups that want monitoring designs that are both cheaper and statistically defensible.