Reducing the rate of false absences of cryptic species in inventory and sampling work
When doing inventory for cryptic and rare species, it can be difficult to determine with great confidence that a sampled area has no occurrences of the target species. Boreal Felt lichen (Erioderma pedicellatum (Hue.) P.M.Jørg.) and Vole Ears lichen (Erioderma mollissimum (G.Sampaio) Du Rietz) are t...
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The American Bryological and Lichenological Society
2019
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ftbioone:10.1639/0007-2745-122.4.578 2023-07-30T04:05:03+02:00 Reducing the rate of false absences of cryptic species in inventory and sampling work Patrick Lauriault Yolanda F. Wiersma Patrick Lauriault Yolanda F. Wiersma world 2019-11-04 text/HTML https://doi.org/10.1639/0007-2745-122.4.578 en eng The American Bryological and Lichenological Society doi:10.1639/0007-2745-122.4.578 All rights reserved. https://doi.org/10.1639/0007-2745-122.4.578 Text 2019 ftbioone https://doi.org/10.1639/0007-2745-122.4.578 2023-07-09T10:59:20Z When doing inventory for cryptic and rare species, it can be difficult to determine with great confidence that a sampled area has no occurrences of the target species. Boreal Felt lichen (Erioderma pedicellatum (Hue.) P.M.Jørg.) and Vole Ears lichen (Erioderma mollissimum (G.Sampaio) Du Rietz) are two rare species of cyanolichens that have several populations in North America, including Nova Scotia, Newfoundland and Alaska. These lichens occur in small numbers and are difficult to spot with the untrained eye; therefore, they are likely to be overlooked in standard sampling protocols. In this paper, we develop and test a sampling method that enables us to determine with confidence that a sample site has zero occurrences of the species of interest within a defined area (i.e., an absence of detections indicates an absence of the target lichen species and is not a false absence). On 50 sites, we randomly assigned “decoy lichen” treatments (small pieces of felt that resemble boreal felt lichen) and three seekers with different survey experience and time limits carried out their respective searches for these decoys. This sampling method is very applicable to sessile, rare organisms, such as lichens and mosses. Using circular sample plots of 5m in radius, we determined that 20 minutes is the required search effort to detect at least one rare and cryptic lichen individuals within the plot. We also found that decoy density on a plot had a strong influence on decoy detectability, regardless of seeker experience. Detection reliability was greater for the two seekers with prior cryptic survey experience compared to the seeker with none. High confidence in the “true absence” rate is useful for comparative studies of optimal and non-optimal habitat, and the methods here are useful to estimate detection rates for other cryptic organisms. Text Newfoundland Alaska BioOne Online Journals The Bryologist 122 4 578 |
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English |
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When doing inventory for cryptic and rare species, it can be difficult to determine with great confidence that a sampled area has no occurrences of the target species. Boreal Felt lichen (Erioderma pedicellatum (Hue.) P.M.Jørg.) and Vole Ears lichen (Erioderma mollissimum (G.Sampaio) Du Rietz) are two rare species of cyanolichens that have several populations in North America, including Nova Scotia, Newfoundland and Alaska. These lichens occur in small numbers and are difficult to spot with the untrained eye; therefore, they are likely to be overlooked in standard sampling protocols. In this paper, we develop and test a sampling method that enables us to determine with confidence that a sample site has zero occurrences of the species of interest within a defined area (i.e., an absence of detections indicates an absence of the target lichen species and is not a false absence). On 50 sites, we randomly assigned “decoy lichen” treatments (small pieces of felt that resemble boreal felt lichen) and three seekers with different survey experience and time limits carried out their respective searches for these decoys. This sampling method is very applicable to sessile, rare organisms, such as lichens and mosses. Using circular sample plots of 5m in radius, we determined that 20 minutes is the required search effort to detect at least one rare and cryptic lichen individuals within the plot. We also found that decoy density on a plot had a strong influence on decoy detectability, regardless of seeker experience. Detection reliability was greater for the two seekers with prior cryptic survey experience compared to the seeker with none. High confidence in the “true absence” rate is useful for comparative studies of optimal and non-optimal habitat, and the methods here are useful to estimate detection rates for other cryptic organisms. |
author2 |
Patrick Lauriault Yolanda F. Wiersma |
format |
Text |
author |
Patrick Lauriault Yolanda F. Wiersma |
spellingShingle |
Patrick Lauriault Yolanda F. Wiersma Reducing the rate of false absences of cryptic species in inventory and sampling work |
author_facet |
Patrick Lauriault Yolanda F. Wiersma |
author_sort |
Patrick Lauriault |
title |
Reducing the rate of false absences of cryptic species in inventory and sampling work |
title_short |
Reducing the rate of false absences of cryptic species in inventory and sampling work |
title_full |
Reducing the rate of false absences of cryptic species in inventory and sampling work |
title_fullStr |
Reducing the rate of false absences of cryptic species in inventory and sampling work |
title_full_unstemmed |
Reducing the rate of false absences of cryptic species in inventory and sampling work |
title_sort |
reducing the rate of false absences of cryptic species in inventory and sampling work |
publisher |
The American Bryological and Lichenological Society |
publishDate |
2019 |
url |
https://doi.org/10.1639/0007-2745-122.4.578 |
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world |
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Newfoundland Alaska |
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Newfoundland Alaska |
op_source |
https://doi.org/10.1639/0007-2745-122.4.578 |
op_relation |
doi:10.1639/0007-2745-122.4.578 |
op_rights |
All rights reserved. |
op_doi |
https://doi.org/10.1639/0007-2745-122.4.578 |
container_title |
The Bryologist |
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122 |
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4 |
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578 |
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1772816759914496000 |