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WK-5:
An introduction to state-space models for population viability analysis
Sunday, August 7,
8 AM - 5 PM
,
McGill
University
Computer Lab
Fee:
$35 US Dollars per person – includes coffee and pastry before departure
to lab, computer lab, training, and handouts. Does not include lunch.
Minimum:
10
Maximum: 30
Organizers:
Elizabeth Holmes (eli.holmes@noaa.gov),
Chris Jordan
Description:
Diffusion
approximation approaches have a prominent place in conservation biology as a
quantitative tool enabling calculation of population viability risk metrics from
simple count data of the sort collected for species of conservation concern.
Typical data collected for such species often has numerous problems –
measurement error, variability from age-structure changes, variability from
density-dependent feedback, environmental cycles, spatially erratic sampling,
etc. State-space approaches have been developed for maximum likelihood
estimation of stochastic density-dependent and density-independent population
models. This workshop will provide an introduction to the use of state-space
models for analyzing spatially structured and unstructured time series data. The
morning will focus on the theory and particular emphasis will be given to the
proper specification of the uncertainty inherent in estimation of risk metrics.
The afternoon will focus on case studies and introduce participants to a
software package used to apply these methods to actual data. Case studies will
include examples of these methods used in Biological Reviews and Status Reviews
for
Pacific Northwest
endangered salmon, Pacific Northwest Herring, and endangered sea turtles. The
workshop will be directed towards the application of these methods for
estimating population viability risk metrics. Students need a basic familiarity
with population models and likelihood functions.
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