Quantifying apparent impact and distinguishing impact from invasiveness in multispecies plant invasions

Autores
Pearson, Dean; Ortega, Yvette K.; Eren, Ozkan; Hierro, Jose Luis
Año de publicación
2016
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
The quantification of invader impacts remains a major hurdle to understanding and managing invasions. Here, we demonstrate a method for quantifying the community-level impact of multiple plant invaders by applying Parker et al.'s (1999) equation (impact = range × local abundance × per capita effect or per unit effect) using data from 620 survey plots from 31 grasslands across west-central Montana, USA. In testing for interactive effects of multiple invaders on native plant abundance (percent cover), we found no evidence for invasional meltdown or synergistic interactions for the 25 exotics tested. While much concern exists regarding impact thresholds, we also found little evidence for nonlinear relationships between invader abundance and impacts. These results suggest that management actions that reduce invader abundance should reduce invader impacts monotonically in this system. Eleven of 25 invaders had significant per unit impacts (negative local-scale relationships between invader and native cover). In decomposing the components of impact, we found that local invader abundance had a significant influence on the likelihood of impact, but range (number of plots occupied) did not. This analysis helped to differentiate measures of invasiveness (local abundance and range) from impact to distinguish high-impact invaders from invaders that exhibit negligible impacts, even when widespread. Distinguishing between high- and low-impact invaders should help refine trait-based prediction of problem species. Despite the unique information derived from evaluation of per unit effects of invaders, invasiveness scores based on range and local abundance produced similar rankings to impact scores that incorporated estimates of per unit effects. Hence, information on range and local abundance alone was sufficient to identify problematic plant invaders at the regional scale. In comparing empirical data on invader impacts to the state noxious weed list, we found that the noxious weed list captured 45% of the high-impact invaders but missed 55% and assigned the lowest risk category to the highest-impact invader. While such subjective weed lists help to guide invasive species management, empirical data are needed to develop more comprehensive rankings of ecological impacts. Using weed lists to classify invaders for testing invasion theory is not well supported.
Fil: Pearson, Dean. University of Montana; Estados Unidos. United States Department of Agriculture; Estados Unidos
Fil: Ortega, Yvette K.. United States Department of Agriculture; Estados Unidos. University of Montana; Estados Unidos
Fil: Eren, Ozkan. Adnan Menderes Universitesi; Turquía
Fil: Hierro, Jose Luis. Consejo Nacional de Investigaciones Científicas y Técnicas. Instituto de Ciencias de la Tierra y Ambientales de La Pampa. Universidad Nacional de La Pampa. Facultad de Ciencias Exactas y Naturales. Instituto de Ciencias de la Tierra y Ambientales de La Pampa; Argentina
Materia
Bromus Tectorum
Centaurea Stoebe
Invader Impact
Invasion Thresholds
Invasional Meltdown
Invasiveness
Montana
Estados Unidos
Noxious Weed Lists
Weed Impact Rankings
Nivel de accesibilidad
acceso abierto
Condiciones de uso
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
Repositorio
CONICET Digital (CONICET)
Institución
Consejo Nacional de Investigaciones Científicas y Técnicas
OAI Identificador
oai:ri.conicet.gov.ar:11336/19356

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oai_identifier_str oai:ri.conicet.gov.ar:11336/19356
network_acronym_str CONICETDig
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network_name_str CONICET Digital (CONICET)
spelling Quantifying apparent impact and distinguishing impact from invasiveness in multispecies plant invasionsPearson, DeanOrtega, Yvette K.Eren, OzkanHierro, Jose LuisBromus TectorumCentaurea StoebeInvader ImpactInvasion ThresholdsInvasional MeltdownInvasivenessMontanaEstados UnidosNoxious Weed ListsWeed Impact Rankingshttps://purl.org/becyt/ford/1.6https://purl.org/becyt/ford/1The quantification of invader impacts remains a major hurdle to understanding and managing invasions. Here, we demonstrate a method for quantifying the community-level impact of multiple plant invaders by applying Parker et al.'s (1999) equation (impact = range × local abundance × per capita effect or per unit effect) using data from 620 survey plots from 31 grasslands across west-central Montana, USA. In testing for interactive effects of multiple invaders on native plant abundance (percent cover), we found no evidence for invasional meltdown or synergistic interactions for the 25 exotics tested. While much concern exists regarding impact thresholds, we also found little evidence for nonlinear relationships between invader abundance and impacts. These results suggest that management actions that reduce invader abundance should reduce invader impacts monotonically in this system. Eleven of 25 invaders had significant per unit impacts (negative local-scale relationships between invader and native cover). In decomposing the components of impact, we found that local invader abundance had a significant influence on the likelihood of impact, but range (number of plots occupied) did not. This analysis helped to differentiate measures of invasiveness (local abundance and range) from impact to distinguish high-impact invaders from invaders that exhibit negligible impacts, even when widespread. Distinguishing between high- and low-impact invaders should help refine trait-based prediction of problem species. Despite the unique information derived from evaluation of per unit effects of invaders, invasiveness scores based on range and local abundance produced similar rankings to impact scores that incorporated estimates of per unit effects. Hence, information on range and local abundance alone was sufficient to identify problematic plant invaders at the regional scale. In comparing empirical data on invader impacts to the state noxious weed list, we found that the noxious weed list captured 45% of the high-impact invaders but missed 55% and assigned the lowest risk category to the highest-impact invader. While such subjective weed lists help to guide invasive species management, empirical data are needed to develop more comprehensive rankings of ecological impacts. Using weed lists to classify invaders for testing invasion theory is not well supported.Fil: Pearson, Dean. University of Montana; Estados Unidos. United States Department of Agriculture; Estados UnidosFil: Ortega, Yvette K.. United States Department of Agriculture; Estados Unidos. University of Montana; Estados UnidosFil: Eren, Ozkan. Adnan Menderes Universitesi; TurquíaFil: Hierro, Jose Luis. Consejo Nacional de Investigaciones Científicas y Técnicas. Instituto de Ciencias de la Tierra y Ambientales de La Pampa. Universidad Nacional de La Pampa. Facultad de Ciencias Exactas y Naturales. Instituto de Ciencias de la Tierra y Ambientales de La Pampa; ArgentinaWiley2016-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/19356Pearson, Dean; Ortega, Yvette K.; Eren, Ozkan; Hierro, Jose Luis; Quantifying apparent impact and distinguishing impact from invasiveness in multispecies plant invasions; Wiley; Ecological Applications; 26; 1; 1-2016; 162-1731051-0761CONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/doi/10.1890/14-2345info:eu-repo/semantics/altIdentifier/url/http://onlinelibrary.wiley.com/doi/10.1890/14-2345/abstractinfo:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-sa/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-09-29T09:36:51Zoai:ri.conicet.gov.ar:11336/19356instacron:CONICETInstitucionalhttp://ri.conicet.gov.ar/Organismo científico-tecnológicoNo correspondehttp://ri.conicet.gov.ar/oai/requestdasensio@conicet.gov.ar; lcarlino@conicet.gov.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:34982025-09-29 09:36:51.777CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv Quantifying apparent impact and distinguishing impact from invasiveness in multispecies plant invasions
title Quantifying apparent impact and distinguishing impact from invasiveness in multispecies plant invasions
spellingShingle Quantifying apparent impact and distinguishing impact from invasiveness in multispecies plant invasions
Pearson, Dean
Bromus Tectorum
Centaurea Stoebe
Invader Impact
Invasion Thresholds
Invasional Meltdown
Invasiveness
Montana
Estados Unidos
Noxious Weed Lists
Weed Impact Rankings
title_short Quantifying apparent impact and distinguishing impact from invasiveness in multispecies plant invasions
title_full Quantifying apparent impact and distinguishing impact from invasiveness in multispecies plant invasions
title_fullStr Quantifying apparent impact and distinguishing impact from invasiveness in multispecies plant invasions
title_full_unstemmed Quantifying apparent impact and distinguishing impact from invasiveness in multispecies plant invasions
title_sort Quantifying apparent impact and distinguishing impact from invasiveness in multispecies plant invasions
dc.creator.none.fl_str_mv Pearson, Dean
Ortega, Yvette K.
Eren, Ozkan
Hierro, Jose Luis
author Pearson, Dean
author_facet Pearson, Dean
Ortega, Yvette K.
Eren, Ozkan
Hierro, Jose Luis
author_role author
author2 Ortega, Yvette K.
Eren, Ozkan
Hierro, Jose Luis
author2_role author
author
author
dc.subject.none.fl_str_mv Bromus Tectorum
Centaurea Stoebe
Invader Impact
Invasion Thresholds
Invasional Meltdown
Invasiveness
Montana
Estados Unidos
Noxious Weed Lists
Weed Impact Rankings
topic Bromus Tectorum
Centaurea Stoebe
Invader Impact
Invasion Thresholds
Invasional Meltdown
Invasiveness
Montana
Estados Unidos
Noxious Weed Lists
Weed Impact Rankings
purl_subject.fl_str_mv https://purl.org/becyt/ford/1.6
https://purl.org/becyt/ford/1
dc.description.none.fl_txt_mv The quantification of invader impacts remains a major hurdle to understanding and managing invasions. Here, we demonstrate a method for quantifying the community-level impact of multiple plant invaders by applying Parker et al.'s (1999) equation (impact = range × local abundance × per capita effect or per unit effect) using data from 620 survey plots from 31 grasslands across west-central Montana, USA. In testing for interactive effects of multiple invaders on native plant abundance (percent cover), we found no evidence for invasional meltdown or synergistic interactions for the 25 exotics tested. While much concern exists regarding impact thresholds, we also found little evidence for nonlinear relationships between invader abundance and impacts. These results suggest that management actions that reduce invader abundance should reduce invader impacts monotonically in this system. Eleven of 25 invaders had significant per unit impacts (negative local-scale relationships between invader and native cover). In decomposing the components of impact, we found that local invader abundance had a significant influence on the likelihood of impact, but range (number of plots occupied) did not. This analysis helped to differentiate measures of invasiveness (local abundance and range) from impact to distinguish high-impact invaders from invaders that exhibit negligible impacts, even when widespread. Distinguishing between high- and low-impact invaders should help refine trait-based prediction of problem species. Despite the unique information derived from evaluation of per unit effects of invaders, invasiveness scores based on range and local abundance produced similar rankings to impact scores that incorporated estimates of per unit effects. Hence, information on range and local abundance alone was sufficient to identify problematic plant invaders at the regional scale. In comparing empirical data on invader impacts to the state noxious weed list, we found that the noxious weed list captured 45% of the high-impact invaders but missed 55% and assigned the lowest risk category to the highest-impact invader. While such subjective weed lists help to guide invasive species management, empirical data are needed to develop more comprehensive rankings of ecological impacts. Using weed lists to classify invaders for testing invasion theory is not well supported.
Fil: Pearson, Dean. University of Montana; Estados Unidos. United States Department of Agriculture; Estados Unidos
Fil: Ortega, Yvette K.. United States Department of Agriculture; Estados Unidos. University of Montana; Estados Unidos
Fil: Eren, Ozkan. Adnan Menderes Universitesi; Turquía
Fil: Hierro, Jose Luis. Consejo Nacional de Investigaciones Científicas y Técnicas. Instituto de Ciencias de la Tierra y Ambientales de La Pampa. Universidad Nacional de La Pampa. Facultad de Ciencias Exactas y Naturales. Instituto de Ciencias de la Tierra y Ambientales de La Pampa; Argentina
description The quantification of invader impacts remains a major hurdle to understanding and managing invasions. Here, we demonstrate a method for quantifying the community-level impact of multiple plant invaders by applying Parker et al.'s (1999) equation (impact = range × local abundance × per capita effect or per unit effect) using data from 620 survey plots from 31 grasslands across west-central Montana, USA. In testing for interactive effects of multiple invaders on native plant abundance (percent cover), we found no evidence for invasional meltdown or synergistic interactions for the 25 exotics tested. While much concern exists regarding impact thresholds, we also found little evidence for nonlinear relationships between invader abundance and impacts. These results suggest that management actions that reduce invader abundance should reduce invader impacts monotonically in this system. Eleven of 25 invaders had significant per unit impacts (negative local-scale relationships between invader and native cover). In decomposing the components of impact, we found that local invader abundance had a significant influence on the likelihood of impact, but range (number of plots occupied) did not. This analysis helped to differentiate measures of invasiveness (local abundance and range) from impact to distinguish high-impact invaders from invaders that exhibit negligible impacts, even when widespread. Distinguishing between high- and low-impact invaders should help refine trait-based prediction of problem species. Despite the unique information derived from evaluation of per unit effects of invaders, invasiveness scores based on range and local abundance produced similar rankings to impact scores that incorporated estimates of per unit effects. Hence, information on range and local abundance alone was sufficient to identify problematic plant invaders at the regional scale. In comparing empirical data on invader impacts to the state noxious weed list, we found that the noxious weed list captured 45% of the high-impact invaders but missed 55% and assigned the lowest risk category to the highest-impact invader. While such subjective weed lists help to guide invasive species management, empirical data are needed to develop more comprehensive rankings of ecological impacts. Using weed lists to classify invaders for testing invasion theory is not well supported.
publishDate 2016
dc.date.none.fl_str_mv 2016-01
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
http://purl.org/coar/resource_type/c_6501
info:ar-repo/semantics/articulo
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv http://hdl.handle.net/11336/19356
Pearson, Dean; Ortega, Yvette K.; Eren, Ozkan; Hierro, Jose Luis; Quantifying apparent impact and distinguishing impact from invasiveness in multispecies plant invasions; Wiley; Ecological Applications; 26; 1; 1-2016; 162-173
1051-0761
CONICET Digital
CONICET
url http://hdl.handle.net/11336/19356
identifier_str_mv Pearson, Dean; Ortega, Yvette K.; Eren, Ozkan; Hierro, Jose Luis; Quantifying apparent impact and distinguishing impact from invasiveness in multispecies plant invasions; Wiley; Ecological Applications; 26; 1; 1-2016; 162-173
1051-0761
CONICET Digital
CONICET
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/doi/10.1890/14-2345
info:eu-repo/semantics/altIdentifier/url/http://onlinelibrary.wiley.com/doi/10.1890/14-2345/abstract
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
eu_rights_str_mv openAccess
rights_invalid_str_mv https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
dc.format.none.fl_str_mv application/pdf
application/pdf
dc.publisher.none.fl_str_mv Wiley
publisher.none.fl_str_mv Wiley
dc.source.none.fl_str_mv reponame:CONICET Digital (CONICET)
instname:Consejo Nacional de Investigaciones Científicas y Técnicas
reponame_str CONICET Digital (CONICET)
collection CONICET Digital (CONICET)
instname_str Consejo Nacional de Investigaciones Científicas y Técnicas
repository.name.fl_str_mv CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicas
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