Available time-series of terrestrial animals provide low reliability in population trend estimates
Year: 2026
Type: preprint
Abstract: Monitoring biodiversity through time is critical for understanding the impacts of global change, yet the reliability of available time-series for estimating population trends remains poorly studied. We simulated population dynamics to study how monitoring duration, inter-annual variability, and temporal autocorrelation influence trend reliability. We then inferred the expected reliability of 16,450 empirical time-series of terrestrial animals based on those simulations. Longer, less variable, and negatively autocorrelated time-series produced more reliable trend estimates. Time-series shorter than 20 years led to large magnitude errors and low power in estimating population trends, despite generally low sign uncertainty. Overall, 80% of the empirical time-series were too short and/or noisy to identify meaningful temporal trends, yet reliability varies among taxa. Our results show important limitations in the available biodiversity data, stressing the need to sustain long-term monitoring to better estimate population trends, a top priority in the current biodiversity crisis.
Language: English
Subfield: Ecology
Field: Environmental Science
Domain: Physical Sciences
SDG: Life on land
Open Access status: green
Funders: Innovationsfonden, Biodiversa+, European Commission, Deutsche Forschungsgemeinschaft, Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung, Bundesministerium für Bildung und Forschung, Nederlandse Organisatie voor Wetenschappelijk Onderzoek, Agencia Estatal de Investigación
OpenAlex ID: W7222482910