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
- Institución
- Consejo Nacional de Investigaciones Científicas y Técnicas
- OAI Identificador
- oai:ri.conicet.gov.ar:11336/97136
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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 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/11336/97136 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 |
dc.relation.none.fl_str_mv |
info:eu-repo/semantics/altIdentifier/url/https://link.springer.com/article/10.1007/s10531-018-1527-9 info:eu-repo/semantics/altIdentifier/doi/10.1007/s10531-018-1527-9 |
dc.rights.none.fl_str_mv |
info:eu-repo/semantics/openAccess https://creativecommons.org/licenses/by-nc-sa/2.5/ar/ |
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openAccess |
rights_invalid_str_mv |
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/ |
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application/pdf application/pdf |
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Springer |
publisher.none.fl_str_mv |
Springer |
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reponame:CONICET Digital (CONICET) instname:Consejo Nacional de Investigaciones Científicas y Técnicas |
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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 |