# Spatiotemporal Population Growth Patterns and Interactions Among Sympatric Central European Mesocarnivores

## TL;DR

This study examines how three mesocarnivores in Hungary coexist and grow over time, finding minimal competition despite the golden jackal's expansion.

## Contribution

The study provides new insights into coexistence mechanisms among sympatric mesocarnivores using long-term population data.

## Key findings

- Golden jackals, red foxes, and badgers showed weak to moderate positive population growth rate associations.
- No evidence of golden jackal suppression of foxes or badgers was found.
- Badgers showed the strongest positive association with fox populations.

## Abstract

Understanding interactions among sympatric mesocarnivore populations is essential for making sound management decisions. The golden jackal has rapidly expanded in Europe, raising questions about its potential intraguild effects. Using long-term hunting bag data (1997–2024) from Hungary, we investigated spatiotemporal population trends of the European badger, red fox, and golden jackal. We examined pairwise associations in their annual growth rates. Generalised additive models and Pearson correlation analyses revealed strong species-specific temporal and spatial trends and weak to moderate positive relationships among the species’ population growth rates at the national scale and within regions of high jackal population density. We found no evidence of jackal suppression of foxes or badgers. Additionally, badgers showed the strongest positive association with fox populations. Our large-scale analyses suggest that these mesocarnivores coexist without substantial competitive interference, likely due to local spatial heterogeneity and fine-scale temporal partitioning that are not detectable in annual, broad-scale (national) data. These findings highlight the importance of integrating broad-scale population data with finer-scale behavioural studies to better understand coexistence mechanisms in expanding mesocarnivore assemblages.