Early detection monitoring for non-indigenous fishes; comparison of survey approaches during two species introductions in a Great Lakes port.
Biol Invasions
; 24: 463-478, 2021 Dec 13.
Article
em En
| MEDLINE
| ID: mdl-35356708
Assessing relative performance of different sampling methods used for early detection monitoring (EDM) is a critical step in understanding the likelihood of detecting new non-indigenous species (NIS) in an environment of interest. EDM performance metrics are typically based on the probability of detecting established NIS or rare indigenous species; however, detection probability estimates for these proxies may not accurately reflect survey effectiveness for newly introduced NIS. We used data from three different EDM survey approaches that varied by targeted life-stage (adult-juvenile versus ichthyoplankton), media (physical fish versus environmental DNA), and taxonomic method (morphology-based versus DNA-based taxonomy) to explore relative detection sensitivity for recently introduced white bass (Morone chrysops) and gizzard shad (Dorosoma cepedianum) in the Port of Duluth-Superior, a NIS introduction hot spot within the Laurentian Great Lakes. Detection efficiency, measured by the effort (number of samples) required to achieve 95% probability of detection, differed by EDM approach and species. Also, the relative sensitivity (detection rate) of each survey approach differed by species. For both species, detection in surveys using DNA-based taxonomy was generally as good or better than the adult-juvenile survey using morphology-based taxonomy. While both species appear to have been detected at early stages of invasion, white bass were likely present up to 5 years prior to initial detection, whereas gizzard shad may have been detected in the first year of introduction. We conclude that using complimentary sampling methods can help to balance the strengths and weaknesses of each approach and provide more reliable early detection of new invaders.
Texto completo:
1
Coleções:
01-internacional
Base de dados:
MEDLINE
Tipo de estudo:
Diagnostic_studies
/
Screening_studies
Idioma:
En
Revista:
Biol Invasions
Ano de publicação:
2021
Tipo de documento:
Article
País de afiliação:
Estados Unidos