Wolverine Spatial Capture-Recapture Data Across Norway

Data supports a Bayesian spatial capture-recapture (SCR) model using Local Evaluation of the State-Space (LESS) to estimate animal density. The study maps wolverine (Gulo gulo) density across the species' entire range in Norway, covering over 200,000 km². The LESS method reduced model computation time by up to 57-fold in simulations.

Use Cases

• Calibrate the Local Evaluation of State-Space (LESS) window parameters for unbiased SCR parameter estimation
• Map wolverine (Gulo gulo) density using SCR models across a 200,000 km² spatial extent
• Validate SCR model performance by comparing estimates from LESS to traditional methods
• Analyze the relationship between the scale parameter (σ) and home range size for spatial ecology studies

Strengths

• Covers the entire known range of wolverines in Norway, spanning over 200,000 km²
• Demonstrates a computational speed increase of up to 57-fold using the LESS method
• Provides a framework for unbiased parameter estimation when AC window width is ≥5σ

Limitations

• The specific data format, column structure, and row count are not provided
• Data is focused on a single species (wolverine) and geographic region (Norway), limiting generalizability
• Relies on prior knowledge of species' home range size for LESS window configuration

Provenance

Source

Dryad digital repository.

Collection Method

Spatial capture-recapture (SCR) data collection and analysis using a Bayesian LESS model.

Freshness

Last updated in June 2020.

Geography

Norway.