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Hide‐and‐seek in vegetation: time‐to‐detection is an efficient design for estimating detectability and occurrence
Author(s) -
Bornand Christophe N.,
Kéry Marc,
Bueche Lena,
Fischer Markus
Publication year - 2014
Publication title -
methods in ecology and evolution
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.425
H-Index - 105
ISSN - 2041-210X
DOI - 10.1111/2041-210x.12171
Subject(s) - occupancy , quadrat , abundance (ecology) , computer science , statistics , reliability (semiconductor) , statistical power , environmental science , ecology , mathematics , power (physics) , biology , shrub , physics , quantum mechanics
SummaryEcology and conservation require reliable data on the occurrence of animals and plants. A major source of bias is imperfect detection, which, however, can be corrected for by estimation of detectability. In traditional occupancy models, this requires repeat or multi‐observer surveys. Recently, time‐to‐detection models have been developed as a cost‐effective alternative, which requires no repeat surveys and hence costs could be halved. We compared the efficiency and reliability of time‐to‐detection and traditional occupancy models under varying survey effort. Two observers independently searched for 17 plant species in 44 100 m 2 Swiss grassland quadrats and recorded the time‐to‐detection for each species, enabling detectability to be estimated with both time‐to‐detection and traditional occupancy models. In addition, we gauged the relative influence on detectability of species, observer, plant height and two measures of abundance (cover and frequency). Estimates of detectability and occupancy under both models were very similar. Rare species were more likely to be overlooked; detectability was strongly affected by abundance. As a measure of abundance, frequency outperformed cover in its predictive power. The two observers differed significantly in their detection ability. Time‐to‐detection models were as accurate as traditional occupancy models, but their data easier to obtain; thus they provide a cost‐effective alternative to traditional occupancy models for detection‐corrected estimation of occurrence.