An approach for using multiple indices for monitoring long-term trends of mesopredators at broad spatial scales

Keyphrases

• Bayesian State-space Model 33%
• Broad Spatial Scale 100%
• Coyote 33%
• Distribution Pattern 33%
• Drastic Change 33%
• General Trends 33%
• Gray Fox 33%
• Harvest Data 33%
• Hunters 33%
• Illinois 33%
• Long-term Trends 100%
• Mesopredator 100%
• Midwestern USA 33%
• Multiple Indices 100%
• Negative Trend 33%
• Observation Error 100%
• Positive Trend 33%
• Raccoon 33%
• Red Fox 33%
• Relative Abundance Index 33%
• Roadkill 33%
• Sampling Methods 66%
• Sampling Variability 66%
• Short Time Series 33%
• Skunk 33%
• Spatiotemporal Pattern 33%
• Spotlight Surveys 33%
• State-space Model 33%
• Temporal Change 33%
• Trapper 100%
• Trend Direction 33%
• Trend Magnitude 33%
• Wildlife 33%

Earth and Planetary Sciences

• Illinois 50%
• Long-Term Trend 100%
• Roadkill 50%
• Spatiotemporal Patterns 50%
• Time Series 50%
• United States of America 100%