Fernando Colchero
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Animal population dynamics

In the last few decades we have witnessed an increase in the development of statistical and computational methods that facilitate the analysis of complex temporal processes. State-space models are amongst the most widely used methods to analyse time series data where observations are obtained with error (De Jong 1988, Jøgersen 2007). These models have been used on a range of applications, such as image processing (Smith and Brown 2003, Riera et al. 2004), fisheries (Millar and Meyer 2000, Nielsen and Berg 2014), and animal population modelling (Clark and Bjørnstad 2004, Colchero et al. 2009).

Fernando Colchero
Fernando Colchero

To understand the effect environmental perturbations, density dependence and exploitation on animal population growth, we have extended Clark and Bjørnstad's (Clark & Bjørnstad 2004 Ecology, 85: 3140-3150) Bayesian state space model to accomodate extractions and different distrubutions for the process and data models. We have applied these methods to datasets from different populations such as desert bighorn sheep (Ovis canadensis) from the Tiburón Island in México (Colchero et al. 2009), Guancos (Lama guanicoe) in Tierra del Fuego, Chile (Zubillaga et al. 2014), or bison (Bison bison) in Northern USA (Koons et al. 2015).

Fernando Colchero