Literature DB >> 25155009

Incorporating detectability of threatened species into environmental impact assessment.

Georgia E Garrard1, Sarah A Bekessy, Michael A McCarthy, Brendan A Wintle.   

Abstract

Environmental impact assessment (EIA) is a key mechanism for protecting threatened plant and animal species. Many species are not perfectly detectable and, even when present, may remain undetected during EIA surveys, increasing the risk of site-level loss or extinction of species. Numerous methods now exist for estimating detectability of plants and animals. Despite this, regulations concerning survey protocol and effort during EIAs fail to adequately address issues of detectability. Probability of detection is intrinsically linked to survey effort; thus, minimum survey effort requirements are a useful way to address the risks of false absences. We utilized 2 methods for determining appropriate survey effort requirements during EIA surveys. One method determined the survey effort required to achieve a probability of detection of 0.95 when the species is present. The second method estimated the survey effort required to either detect the species or reduce the probability of presence to 0.05. We applied these methods to Pimelea spinscens subsp. spinescens, a critically endangered grassland plant species in Melbourne, Australia. We detected P. spinescens in only half of the surveys undertaken at sites where it was known to exist. Estimates of the survey effort required to detect the species or demonstrate its absence with any confidence were much higher than the effort traditionally invested in EIA surveys for this species. We argue that minimum survey requirements be established for all species listed under threatened species legislation and hope that our findings will provide an impetus for collecting, compiling, and synthesizing quantitative detectability estimates for a broad range of plant and animal species.
© 2014 Society for Conservation Biology.

Entities:  

Keywords:  Pimelea spinescens; biological surveys; censos biológicos; falsa ausencia; false absence; tiempo de detección; time to detection

Mesh:

Year:  2014        PMID: 25155009     DOI: 10.1111/cobi.12351

Source DB:  PubMed          Journal:  Conserv Biol        ISSN: 0888-8892            Impact factor:   6.560


  6 in total

1.  Pollen sleuthing for terrestrial plant surveys: Locating plant populations by exploiting pollen movement.

Authors:  Lesley G Campbell; Stephanie J Melles; Eric Vaz; Rebecca J Parker; Kevin S Burgess
Journal:  Appl Plant Sci       Date:  2018-02-08       Impact factor: 1.936

2.  Traditional trapping methods outperform eDNA sampling for introduced semi-aquatic snakes.

Authors:  Jonathan P Rose; Cara Wademan; Suzanne Weir; John S Wood; Brian D Todd
Journal:  PLoS One       Date:  2019-07-02       Impact factor: 3.240

3.  A concise guide to developing and using quantitative models in conservation management.

Authors:  Pablo García-Díaz; Thomas A A Prowse; Dean P Anderson; Miguel Lurgi; Rachelle N Binny; Phillip Cassey
Journal:  Conserv Sci Pract       Date:  2019-04-15

4.  Time-to-detection occupancy methods: performance and utility for improving efficiency of surveys.

Authors:  Brian J Halstead; Jonathan P Rose; Patrick M Kleeman
Journal:  Ecol Appl       Date:  2021-01-27       Impact factor: 4.657

5.  A field experiment characterizing variable detection rates during plant surveys.

Authors:  Cindy E Hauser; Katherine M Giljohann; Michael A McCarthy; Georgia E Garrard; Andrew P Robinson; Nicholas S G Williams; Joslin L Moore
Journal:  Conserv Biol       Date:  2022-01-31       Impact factor: 7.563

6.  Evaluating the effects of laboratory protocols on eDNA detection probability for an endangered freshwater fish.

Authors:  Maxine P Piggott
Journal:  Ecol Evol       Date:  2016-03-17       Impact factor: 2.912

  6 in total

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