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
- Institución
- Consejo Nacional de Investigaciones Científicas y Técnicas
- OAI Identificador
- oai:ri.conicet.gov.ar:11336/19356
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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) |
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CONICET Digital (CONICET) |
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Consejo Nacional de Investigaciones Científicas y Técnicas |
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CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicas |
repository.mail.fl_str_mv |
dasensio@conicet.gov.ar; lcarlino@conicet.gov.ar |
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13.070432 |