Accounting for imperfect detection and survey bias in statistical analysis of presence‐only data

• Published in: Global ecology and biogeography Vol. 23; no. 12; pp. 1472 - 1484
• Main Author: Dorazio, Robert M
• Format: Journal Article
• Language: English
• Published: Oxford Blackwell Science 01.12.2014; Blackwell Publishing Ltd; John Wiley & Sons Ltd; Blackwell; Wiley Subscription Services, Inc
• Subjects: Animal and plant ecology; Animal, plant and microbial ecology; Applied ecology; Bias; Biogeography; Biological and medical sciences; Data models; Ecological modeling; Ecological niche model; ecologists; Estimation bias; Fundamental and applied biological sciences. Psychology; General aspects; MACROECOLOGICAL METHODS; N-mixture model; Opportunistic behavior; Perceptual localization; predictive biogeography; Simulations; site occupancy model; Spatial distribution; Spatial models; spatial point process; species distribution model; Statistical analysis; statistical models; surveys; Synecology; temporal variation; Statistical analysis; Ecological niche model; Biogeography; Ecology; predictive biogeography; species distribution model; site occupancy model; spatial point process; Spatial distribution; N-mixture model; Geographic distribution; Ecological niche; Models; Detection; Distribution range

AIM: During the past decade ecologists have attempted to estimate the parameters of species distribution models by combining locations of species presence observed in opportunistic surveys with spatially referenced covariates of occurrence. Several statistical models have been proposed for the analy...