The University of Southampton
University of Southampton Institutional Repository

Traits influence detection of exotic plant species in tropical forests

Traits influence detection of exotic plant species in tropical forests
Traits influence detection of exotic plant species in tropical forests

Detecting exotic plant species is essential for invasive species management. By accounting for factors likely to affect species’ detection rates (e.g. survey conditions, observer experience), detectability models can help choose search methods and allocate search effort. Integrating information on species’ traits can refine detectability models, and might be particularly valuable if these traits can help improve estimates of detectability where data on particular species are rare. Analysing data collected during line transect distance sampling surveys in Indonesia, we used a multi-species hierarchical distance sampling model to evaluate how plant height, leaf size, leaf shape, and survey location influenced plant species detectability in secondary tropical rainforests. Detectability of the exotic plant species increased with plant height and leaf size. Detectability varied among the different survey locations. We failed to detect a clear effect of leaf shape on detectability. This study indicates that information on traits might improve predictions about exotic species detection, which can then be used to optimise the allocation of search effort for efficient species management. The innovation of the study lies in the multi-species distance sampling model, where the distance-detection function depends on leaf traits and height. The method can be applied elsewhere, including for different traits that may be relevant in other contexts. Trait-based multispecies distance sampling can be a practical approach for sampling exotic shrubs, herbs, or grasses species in the understorey of tropical forests.

1932-6203
1-15
Junaedi, Decky I.
db2d20d5-35b8-4f40-8723-1f637f6804e3
McCarthy, Michael A.
6f8fc0a3-3a74-4691-b38a-982505d4bef0
Guillera-Arroita, Gurutzeta
96e4466d-e078-4748-837e-35ac32cdd86b
Catford, Jane A.
c80a4529-b7cb-4d36-aba8-f38de01ce729
Burgman, Mark A.
e2d9ea05-a5cd-4d0d-b071-6cbf390cd16b
Junaedi, Decky I.
db2d20d5-35b8-4f40-8723-1f637f6804e3
McCarthy, Michael A.
6f8fc0a3-3a74-4691-b38a-982505d4bef0
Guillera-Arroita, Gurutzeta
96e4466d-e078-4748-837e-35ac32cdd86b
Catford, Jane A.
c80a4529-b7cb-4d36-aba8-f38de01ce729
Burgman, Mark A.
e2d9ea05-a5cd-4d0d-b071-6cbf390cd16b

Junaedi, Decky I., McCarthy, Michael A., Guillera-Arroita, Gurutzeta, Catford, Jane A. and Burgman, Mark A. (2018) Traits influence detection of exotic plant species in tropical forests. PLoS ONE, 13 (8), 1-15, [e0202254]. (doi:10.1371/journal.pone.0202254).

Record type: Article

Abstract

Detecting exotic plant species is essential for invasive species management. By accounting for factors likely to affect species’ detection rates (e.g. survey conditions, observer experience), detectability models can help choose search methods and allocate search effort. Integrating information on species’ traits can refine detectability models, and might be particularly valuable if these traits can help improve estimates of detectability where data on particular species are rare. Analysing data collected during line transect distance sampling surveys in Indonesia, we used a multi-species hierarchical distance sampling model to evaluate how plant height, leaf size, leaf shape, and survey location influenced plant species detectability in secondary tropical rainforests. Detectability of the exotic plant species increased with plant height and leaf size. Detectability varied among the different survey locations. We failed to detect a clear effect of leaf shape on detectability. This study indicates that information on traits might improve predictions about exotic species detection, which can then be used to optimise the allocation of search effort for efficient species management. The innovation of the study lies in the multi-species distance sampling model, where the distance-detection function depends on leaf traits and height. The method can be applied elsewhere, including for different traits that may be relevant in other contexts. Trait-based multispecies distance sampling can be a practical approach for sampling exotic shrubs, herbs, or grasses species in the understorey of tropical forests.

Text
journal.pone.0202254 - Version of Record
Available under License Creative Commons Attribution.
Download (11MB)

More information

Accepted/In Press date: 31 July 2018
e-pub ahead of print date: 1 August 2018
Published date: 22 August 2018

Identifiers

Local EPrints ID: 424384
URI: http://eprints.soton.ac.uk/id/eprint/424384
ISSN: 1932-6203
PURE UUID: d81b68bf-53ae-4369-969a-3d5a73fadc8a
ORCID for Jane A. Catford: ORCID iD orcid.org/0000-0003-0582-5960

Catalogue record

Date deposited: 05 Oct 2018 11:36
Last modified: 15 Mar 2024 21:30

Export record

Altmetrics

Contributors

Author: Decky I. Junaedi
Author: Michael A. McCarthy
Author: Gurutzeta Guillera-Arroita
Author: Jane A. Catford ORCID iD
Author: Mark A. Burgman

Download statistics

Downloads from ePrints over the past year. Other digital versions may also be available to download e.g. from the publisher's website.

View more statistics

Atom RSS 1.0 RSS 2.0

Contact ePrints Soton: eprints@soton.ac.uk

ePrints Soton supports OAI 2.0 with a base URL of http://eprints.soton.ac.uk/cgi/oai2

This repository has been built using EPrints software, developed at the University of Southampton, but available to everyone to use.

We use cookies to ensure that we give you the best experience on our website. If you continue without changing your settings, we will assume that you are happy to receive cookies on the University of Southampton website.

×