Applied Hierarchical Modeling in Ecology: Analysis of Distribution, Abundance and Species Richness in R and BUGS

PART 1 MODELS FOR DYNAMIC SYSTEMS1. Relative Abundance Models for Population Dynamics2. Modeling Population Dynamics With Count Data3. Hierarchical Models of Survival4. Modeling Species Distribution and Range Dynamics, and Population Dynamics Using Dynamic Occupancy Models5. Modeling Metacommunity Dynamics Using Dynamic Community Models

PART 2 ADVANCED MODELS6. Multi-state Occupancy Models7. Modeling False Positives8. Modeling Interactions Among Species9. Spatial Models of Distribution and Abundance10. Integrated Models for Multiple Types of Data11. Spatially Explicit Distance Sampling Along Transects12. Conclusions

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• Ambiente
• Ecologia animal
• Ecologia aplicada
• Ecologia das plantas
• Conservação da vida selvagem e do seu habitat

Abundance; Age-structured population model; Asymmetric interaction; Autologistic model; Basis functions; Bioacoustics; CAR model; Citizen science; Colonization; Dail-Madsen model; Dail-Madsen; Data fusion; Density surface models; Detection probability; Directed interaction; Dispersal: spatial DM model; Distribution; Dynamic occupancy model; Extinction; False-positive; False-positive detections; GAM; Generalized additive models; Geostatistical model; GLM; GLMM; Hazard model; Hierarchical distance sampling; Hierarchical model; IM; IPM; JSDM; Machine learning; Misclassification; Occupancy; occupancy; Persistence; Phenology; Population dynamics; Preferential sampling; Range dynamics; Relative abundance; Resource selection; Science-based model; SDM; Spatial autocorrelation; Spatial point process; Species determination; Species distribution model; Species interactions; Stacked data; Stage-structured population model; State-assignment error; State-space model