Reliability of conservation actions based on elasticity analysis of matrix models

L. Scott Mills, Daniel F. Doak, Michael J. Wisdom

Research output: Contribution to journalArticlepeer-review

Abstract

Matrix population models have entered the mainstream of conservation biology, with analysis of proportional sensitivities (elasticity analysis) of demographic rates becoming important components of conservation decision making. We identify areas where management applications using elasticity analysis potentially conflict with the mathematical basis of the technique, and we use a hypothetical example and three real data sets (Prairie Chicken [Tympanuchus cupido], desert tortoise [Gopherus agassizii], and killer whale [Orcinus orca]) to evaluate the extent to which conservation recommendations based on elasticities might be misleading. First, changes in one demographic rate can change the qualitative ranking of the elasticity values calculated from a population matrix, a result that dampens enthusiasm for ranking conservation actions based solely on which rates have the highest elasticity values. Second, although elasticities often provide accurate predictions of future changes in population growth rate under management perturbations that are large or that affect more than one rate concurrently, concordance frequently fails when different rates vary by different amounts. In particular, when vital rates change to their high or low values observed in nature, predictions of future growth rate based on elasticities of a mean matrix can be misleading, even predicting population increase when the population growth rate actually declines following a perturbation. Elasticity measures will continue to be useful tools for applied ecologists, but they should be interpreted with considerable care. We suggest that studies using analytical elasticity analysis explicitly consider the range of variation possible for different rates and that simulation methods are a useful tool to this end.

Original languageEnglish
Pages (from-to)815-829
Number of pages15
JournalConservation Biology
Volume13
Issue number4
DOIs
StatePublished - Aug 1999

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