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Incorporating parametric uncertainty into population viability analysis models

August 23, 2011

Uncertainty in parameter estimates from sampling variation or expert judgment can introduce substantial uncertainty into ecological predictions based on those estimates. However, in standard population viability analyses, one of the most widely used tools for managing plant, fish and wildlife populations, parametric uncertainty is often ignored in or discarded from model projections. We present a method for explicitly incorporating this source of uncertainty into population models to fully account for risk in management and decision contexts. Our method involves a two-step simulation process where parametric uncertainty is incorporated into the replication loop of the model and temporal variance is incorporated into the loop for time steps in the model. Using the piping plover, a federally threatened shorebird in the USA and Canada, as an example, we compare abundance projections and extinction probabilities from simulations that exclude and include parametric uncertainty. Although final abundance was very low for all sets of simulations, estimated extinction risk was much greater for the simulation that incorporated parametric uncertainty in the replication loop. Decisions about species conservation (e.g., listing, delisting, and jeopardy) might differ greatly depending on the treatment of parametric uncertainty in population models.

Citation Information

Publication Year 2011
Title Incorporating parametric uncertainty into population viability analysis models
DOI 10.1016/j.biocon.2011.01.005
Authors Conor P. McGowan, Michael C. Runge, Michael A. Larson
Publication Type Article
Publication Subtype Journal Article
Series Title Biological Conservation
Series Number
Index ID 70004548
Record Source USGS Publications Warehouse
USGS Organization Patuxent Wildlife Research Center