Non-detection errors in a survey of persistent, highly-detectable vegetation species |
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Authors: | Kenneth D Clarke Megan Lewis Robert Brandle Bertram Ostendorf |
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Institution: | (1) Department of Animal Biology, Pavia University, Botta Square 9, 27100 Pavia, Italy; |
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Abstract: | Rare, small or annual vegetation species are widely known to be imperfectly detected with single site surveys by most conventional
vegetation survey methods. However, the detectability of common, persistent vegetation species is assumed to be high, but
without supporting research. In this study, we evaluate the extent of false-negative errors of perennial vegetation species
in a systematic vegetation survey in arid South Australia. Analysis was limited to the seven most easily detected persistent
vegetation species and controlled for observer skill. By comparison of methodologies, we then predict the magnitude of non-detection
error rates in a second survey. The analysis revealed that all but one highly detectable perennial vegetation species was
imperfectly detected (detection probabilities ranged from 0.22 to 0.83). While focussed in the Australian rangelands, the
implications of this study are far reaching. Inferences drawn from systematic vegetation surveys that fail to identify and
account for non-detection errors should be considered potentially flawed. The identification of this problem in vegetation
surveying is long overdue. By comparison, non-detection has been a widely acknowledged, and dealt with, problem in fauna surveying
for decades. We recommend that, where necessary, vegetation survey methodology adopt the methods developed in fauna surveying
to cope with non-detection errors. |
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