Current understanding of invasive species impacts cannot be ignored: potential publication biases do not invalidate findings

Autores
Kuebbing, Sara E.; Nuñez, Martin Andres
Año de publicación
2018
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
Guerin et al. (2017) believe many nonnative species do not cause ecological harm and, therefore, underlying biases towards studying harmful species render meta-analysis unhelpful for designing effective management strategies. Invasion biologists already recognize this bias (Py?ek et al. 2008; Hulme et al. 2013). We argue that meta-analyses are indeed useful for managers for three reasons. First, most meta-analyses explicitly and honestly address bias. Second, for our meta-analysis (Kuebbing and Nuñez 2016), it is unlikely that more even sampling across types of nonnative species would lead to a different conclusion. Finally, and perhaps most importantly, the bias of studying nonnatives with suspected or known impacts focuses research on the exact subset of nonnatives most relevant to managers. It is important to clarify terminology to understand the nature and implications of bias. Ecologists classify nonnative species into three categories: (1) casual nonnatives that do not form self-sustaining populations; (2) naturalized nonnatives that do form self-sustaining populations; (3) invasive nonnatives that form self-sustaining populations and spread beyond their original introduction point (Richardson et al. 2000). There is disagreement whether the definition of invasive should include a negative impact (Young and Larson 2011), but the best available evidence suggests that impacts increase with increasing spread and abundance (Simberlof et al. 2013; Hulme et al. 2013).
Fil: Kuebbing, Sara E.. University of Yale; Estados Unidos
Fil: Nuñez, Martin Andres. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Patagonia Norte. Instituto de Investigaciones en Biodiversidad y Medioambiente. Universidad Nacional del Comahue. Centro Regional Universidad Bariloche. Instituto de Investigaciones en Biodiversidad y Medioambiente; Argentina
Materia
NONNATIVE SPECIES
META-ANALYSIS
INVASIVE SPECIES
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:11336/97136

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spelling Current understanding of invasive species impacts cannot be ignored: potential publication biases do not invalidate findingsKuebbing, Sara E.Nuñez, Martin AndresNONNATIVE SPECIESMETA-ANALYSISINVASIVE SPECIEShttps://purl.org/becyt/ford/1.6https://purl.org/becyt/ford/1Guerin et al. (2017) believe many nonnative species do not cause ecological harm and, therefore, underlying biases towards studying harmful species render meta-analysis unhelpful for designing effective management strategies. Invasion biologists already recognize this bias (Py?ek et al. 2008; Hulme et al. 2013). We argue that meta-analyses are indeed useful for managers for three reasons. First, most meta-analyses explicitly and honestly address bias. Second, for our meta-analysis (Kuebbing and Nuñez 2016), it is unlikely that more even sampling across types of nonnative species would lead to a different conclusion. Finally, and perhaps most importantly, the bias of studying nonnatives with suspected or known impacts focuses research on the exact subset of nonnatives most relevant to managers. It is important to clarify terminology to understand the nature and implications of bias. Ecologists classify nonnative species into three categories: (1) casual nonnatives that do not form self-sustaining populations; (2) naturalized nonnatives that do form self-sustaining populations; (3) invasive nonnatives that form self-sustaining populations and spread beyond their original introduction point (Richardson et al. 2000). There is disagreement whether the definition of invasive should include a negative impact (Young and Larson 2011), but the best available evidence suggests that impacts increase with increasing spread and abundance (Simberlof et al. 2013; Hulme et al. 2013).Fil: Kuebbing, Sara E.. University of Yale; Estados UnidosFil: Nuñez, Martin Andres. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Patagonia Norte. Instituto de Investigaciones en Biodiversidad y Medioambiente. Universidad Nacional del Comahue. Centro Regional Universidad Bariloche. Instituto de Investigaciones en Biodiversidad y Medioambiente; ArgentinaSpringer2018-05info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/97136Kuebbing, Sara E.; Nuñez, Martin Andres; Current understanding of invasive species impacts cannot be ignored: potential publication biases do not invalidate findings; Springer; Biodiversity and Conservation; 27; 6; 5-2018; 1545-15480960-31151572-9710CONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/url/https://link.springer.com/article/10.1007/s10531-018-1527-9info:eu-repo/semantics/altIdentifier/doi/10.1007/s10531-018-1527-9info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-sa/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-09-29T09:33:57Zoai:ri.conicet.gov.ar:11336/97136instacron: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 09:33:58.049CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv Current understanding of invasive species impacts cannot be ignored: potential publication biases do not invalidate findings
title Current understanding of invasive species impacts cannot be ignored: potential publication biases do not invalidate findings
spellingShingle Current understanding of invasive species impacts cannot be ignored: potential publication biases do not invalidate findings
Kuebbing, Sara E.
NONNATIVE SPECIES
META-ANALYSIS
INVASIVE SPECIES
title_short Current understanding of invasive species impacts cannot be ignored: potential publication biases do not invalidate findings
title_full Current understanding of invasive species impacts cannot be ignored: potential publication biases do not invalidate findings
title_fullStr Current understanding of invasive species impacts cannot be ignored: potential publication biases do not invalidate findings
title_full_unstemmed Current understanding of invasive species impacts cannot be ignored: potential publication biases do not invalidate findings
title_sort Current understanding of invasive species impacts cannot be ignored: potential publication biases do not invalidate findings
dc.creator.none.fl_str_mv Kuebbing, Sara E.
Nuñez, Martin Andres
author Kuebbing, Sara E.
author_facet Kuebbing, Sara E.
Nuñez, Martin Andres
author_role author
author2 Nuñez, Martin Andres
author2_role author
dc.subject.none.fl_str_mv NONNATIVE SPECIES
META-ANALYSIS
INVASIVE SPECIES
topic NONNATIVE SPECIES
META-ANALYSIS
INVASIVE SPECIES
purl_subject.fl_str_mv https://purl.org/becyt/ford/1.6
https://purl.org/becyt/ford/1
dc.description.none.fl_txt_mv Guerin et al. (2017) believe many nonnative species do not cause ecological harm and, therefore, underlying biases towards studying harmful species render meta-analysis unhelpful for designing effective management strategies. Invasion biologists already recognize this bias (Py?ek et al. 2008; Hulme et al. 2013). We argue that meta-analyses are indeed useful for managers for three reasons. First, most meta-analyses explicitly and honestly address bias. Second, for our meta-analysis (Kuebbing and Nuñez 2016), it is unlikely that more even sampling across types of nonnative species would lead to a different conclusion. Finally, and perhaps most importantly, the bias of studying nonnatives with suspected or known impacts focuses research on the exact subset of nonnatives most relevant to managers. It is important to clarify terminology to understand the nature and implications of bias. Ecologists classify nonnative species into three categories: (1) casual nonnatives that do not form self-sustaining populations; (2) naturalized nonnatives that do form self-sustaining populations; (3) invasive nonnatives that form self-sustaining populations and spread beyond their original introduction point (Richardson et al. 2000). There is disagreement whether the definition of invasive should include a negative impact (Young and Larson 2011), but the best available evidence suggests that impacts increase with increasing spread and abundance (Simberlof et al. 2013; Hulme et al. 2013).
Fil: Kuebbing, Sara E.. University of Yale; Estados Unidos
Fil: Nuñez, Martin Andres. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Patagonia Norte. Instituto de Investigaciones en Biodiversidad y Medioambiente. Universidad Nacional del Comahue. Centro Regional Universidad Bariloche. Instituto de Investigaciones en Biodiversidad y Medioambiente; Argentina
description Guerin et al. (2017) believe many nonnative species do not cause ecological harm and, therefore, underlying biases towards studying harmful species render meta-analysis unhelpful for designing effective management strategies. Invasion biologists already recognize this bias (Py?ek et al. 2008; Hulme et al. 2013). We argue that meta-analyses are indeed useful for managers for three reasons. First, most meta-analyses explicitly and honestly address bias. Second, for our meta-analysis (Kuebbing and Nuñez 2016), it is unlikely that more even sampling across types of nonnative species would lead to a different conclusion. Finally, and perhaps most importantly, the bias of studying nonnatives with suspected or known impacts focuses research on the exact subset of nonnatives most relevant to managers. It is important to clarify terminology to understand the nature and implications of bias. Ecologists classify nonnative species into three categories: (1) casual nonnatives that do not form self-sustaining populations; (2) naturalized nonnatives that do form self-sustaining populations; (3) invasive nonnatives that form self-sustaining populations and spread beyond their original introduction point (Richardson et al. 2000). There is disagreement whether the definition of invasive should include a negative impact (Young and Larson 2011), but the best available evidence suggests that impacts increase with increasing spread and abundance (Simberlof et al. 2013; Hulme et al. 2013).
publishDate 2018
dc.date.none.fl_str_mv 2018-05
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
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info:ar-repo/semantics/articulo
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv http://hdl.handle.net/11336/97136
Kuebbing, Sara E.; Nuñez, Martin Andres; Current understanding of invasive species impacts cannot be ignored: potential publication biases do not invalidate findings; Springer; Biodiversity and Conservation; 27; 6; 5-2018; 1545-1548
0960-3115
1572-9710
CONICET Digital
CONICET
url http://hdl.handle.net/11336/97136
identifier_str_mv Kuebbing, Sara E.; Nuñez, Martin Andres; Current understanding of invasive species impacts cannot be ignored: potential publication biases do not invalidate findings; Springer; Biodiversity and Conservation; 27; 6; 5-2018; 1545-1548
0960-3115
1572-9710
CONICET Digital
CONICET
dc.language.none.fl_str_mv eng
language eng
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application/pdf
dc.publisher.none.fl_str_mv Springer
publisher.none.fl_str_mv Springer
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