The importance of observation versus process error in analyses of global ungulate populations.

ABSTRACT: Population abundance data vary widely in quality and are rarely accurate. The two main components of error in such data are observation and process error. We used Bayesian state space models to estimate the observation and process error in time-series of 55 globally distributed populations of two species, Cervus elaphus (elk/red deer) and Rangifer tarandus (caribou/reindeer). We examined variation among populations and species in the magnitude of estimates of error components and density dependence using generalized linear models. Process error exceeded observation error in 75% of all populations, and on average, both components of error were greater in Rangifer than in Cervus populations. Observation error differed significantly across the different observation methods, and predation and

SUBMITTER: Ahrestani FS 

PROVIDER: S-EPMC6506149 | biostudies-literature | 2013 Nov

REPOSITORIES: biostudies-literature