Combined Influences of Model Choice, Data Quality, and Data Quantity When Estimating Population Trends.

ABSTRACT: Estimating and projecting population trends using population viability analysis (PVA) are central to identifying species at risk of extinction and for informing conservation management strategies. Models for PVA generally fall within two categories, scalar (count-based) or matrix (demographic). Model structure, process error, measurement error, and time series length all have known impacts in population risk assessments, but their combined impact has not been thoroughly investigated. We tested the ability of scalar and matrix PVA models to predict percent decline over a ten-year interval, selected to coincide with the IUCN Red List criterion A.3, using data simulated for a hypothetical, short-lived organism with a simple life-history and for a threatened snail, Tasmaphena lamproides. PVA p

SUBMITTER: Rueda-Cediel P 

PROVIDER: S-EPMC4503393 | biostudies-literature | 2015

REPOSITORIES: biostudies-literature