title: Presence-absence versus abundance data for monitoring threatened species.
abstract: Effective detection of population trend is crucial for managing threatened species. Little theory exists, however, to assist managers in choosing the most cost-effective monitoring techniques for diagnosing trend. We present a framework for determining the optimal monitoring strategy by simulating a manager collecting data on a declining species, the Chestnut-rumped Hylacola (Hylacola pyrrhopygia parkeri), to determine whether the species should be listed under the IUCN (World Conservation Union) Red List. We compared the efficiencies of two strategies for detecting trend, abundance, and presence-absence surveys, under financial constraints. One might expect the abundance surveys to be superior under all circumstances because more information is collected at each site. Nevertheless, the presence-absence data can be collected at more sites because the surveyor is not obliged to spend a fixed amount of time at each site. The optimal strategy for monitoring was very dependent on the budget available. Under some circumstances, presence-absence surveys outperformed abundance surveys for diagnosing the IUCN Red List categories cost-effectively. Abundance surveys were best if the species was expected to be recorded more than 16 times/year; otherwise, presence-absence surveys were best. The relationship between the strategies we investigated is likely to be relevant for many comparisons of presence-absence or abundance data. Managers of any cryptic or low-density species who hope to maximize their success of estimating trend should find an application for our results.
authors.affiliation: The Ecology Centre, School of Integrative Biology, University of Queensland, St Lucia 4072, Australia. l.joseph@uq.edu.au
authors.forename: Liana N
authors.initials: LN
authors.lastname: Joseph
authors.forename: Scott A
authors.initials: SA
authors.lastname: Field
authors.forename: Chris
authors.initials: C
authors.lastname: Wilcox
authors.forename: Hugh P
authors.initials: HP
authors.lastname: Possingham
mesh_terms: D000818:Animals; D001717:Birds / Q000254:growth & development / Q000502:physiology*; D003198:Computer Simulation; D003247:Conservation of Natural Resources / Q000379:methods* / Q000706:statistics & numerical data; D003362:Cost-Benefit Analysis; D017753:Ecosystem; D004784:Environmental Monitoring; D005260:Female; D008297:Male; D008954:Models, Biological; D015233:Models, Statistical; D011157:Population Dynamics; D011158:Population Growth