Combining correlative and mechanistic niche models with human activity data to elucidate the invasive potential of a sub‐Antarctic insect

Abstract Aim Correlative species distribution models (SDMs) are subject to substantial spatio‐temporal limitations when historical occurrence records of data‐poor species provide incomplete and outdated information for niche modelling. Complementary mechanistic modelling techniques can, therefore, o...

Full description

Bibliographic Details
Published in:Journal of Biogeography
Main Authors: Pertierra, Luis R., Bartlett, Jesamine C., Duffy, Grant A., Vega, Greta C., Hughes, Kevin A., Hayward, Scott A. L., Convey, Peter, Olalla‐Tarraga, Miguel A., Aragón, P.
Other Authors: Natural Environment Research Council, University of Birmingham, British Antarctic Survey
Format: Article in Journal/Newspaper
Language:English
Published: Wiley 2019
Subjects:
Online Access:http://dx.doi.org/10.1111/jbi.13780
https://api.wiley.com/onlinelibrary/tdm/v1/articles/10.1111%2Fjbi.13780
https://onlinelibrary.wiley.com/doi/pdf/10.1111/jbi.13780
https://onlinelibrary.wiley.com/doi/full-xml/10.1111/jbi.13780
id crwiley:10.1111/jbi.13780
record_format openpolar
spelling crwiley:10.1111/jbi.13780 2024-09-15T17:48:45+00:00 Combining correlative and mechanistic niche models with human activity data to elucidate the invasive potential of a sub‐Antarctic insect Pertierra, Luis R. Bartlett, Jesamine C. Duffy, Grant A. Vega, Greta C. Hughes, Kevin A. Hayward, Scott A. L. Convey, Peter Olalla‐Tarraga, Miguel A. Aragón, P. Natural Environment Research Council University of Birmingham British Antarctic Survey 2019 http://dx.doi.org/10.1111/jbi.13780 https://api.wiley.com/onlinelibrary/tdm/v1/articles/10.1111%2Fjbi.13780 https://onlinelibrary.wiley.com/doi/pdf/10.1111/jbi.13780 https://onlinelibrary.wiley.com/doi/full-xml/10.1111/jbi.13780 en eng Wiley http://onlinelibrary.wiley.com/termsAndConditions#vor Journal of Biogeography volume 47, issue 3, page 658-673 ISSN 0305-0270 1365-2699 journal-article 2019 crwiley https://doi.org/10.1111/jbi.13780 2024-08-20T04:16:53Z Abstract Aim Correlative species distribution models (SDMs) are subject to substantial spatio‐temporal limitations when historical occurrence records of data‐poor species provide incomplete and outdated information for niche modelling. Complementary mechanistic modelling techniques can, therefore, offer a valuable contribution to underpin more physiologically informed predictions of biological invasions, the risk of which is often exacerbated by climate change. In this study we integrate physiological and human pressure data to address the uncertainties and limitations of correlative SDMs and to better understand, predict and manage biological invasions. Location Western archipelagos of the Southern Ocean and martime Antarctica. Taxon Eretmoptera murphyi (Chironomidae), invertebrates. Methods Mahalanobis Distances were used for correlative SDM construction for a species with few records. A mechanistic SDM was built around different fitness components (larval survival and life stage progression) as a function of temperature. SDM predictions were combined with human activity levels in Antarctica to generate a site vulnerability index to the assess colonization risk of E. murphyi . Future scenarios of ecophysiological suitability were built around the warming trends in the region. Results Both SDMs converge to predict high environmental suitability in the species' native and introduced ranges. However, the mechanistic model indicates a slightly larger invasive potential based on larval performance at different temperatures. Human activity levels across the Antarctic Peninsula play a key role in discerning site vulnerabilities. Niche suitability in Antarctica grows considerably under long‐term climate scenarios, leading to a substantially higher invasive threat to the Antarctic ecosystems. In turn changing conditions result in growing physiological mismatches with the environment in the native range in South Georgia. Main conclusions Long‐term studies of invasion potential under climate benefit from integrating ... Article in Journal/Newspaper Antarc* Antarctic Antarctic Peninsula Antarctica Southern Ocean Wiley Online Library Journal of Biogeography 47 3 658 673
institution Open Polar
collection Wiley Online Library
op_collection_id crwiley
language English
description Abstract Aim Correlative species distribution models (SDMs) are subject to substantial spatio‐temporal limitations when historical occurrence records of data‐poor species provide incomplete and outdated information for niche modelling. Complementary mechanistic modelling techniques can, therefore, offer a valuable contribution to underpin more physiologically informed predictions of biological invasions, the risk of which is often exacerbated by climate change. In this study we integrate physiological and human pressure data to address the uncertainties and limitations of correlative SDMs and to better understand, predict and manage biological invasions. Location Western archipelagos of the Southern Ocean and martime Antarctica. Taxon Eretmoptera murphyi (Chironomidae), invertebrates. Methods Mahalanobis Distances were used for correlative SDM construction for a species with few records. A mechanistic SDM was built around different fitness components (larval survival and life stage progression) as a function of temperature. SDM predictions were combined with human activity levels in Antarctica to generate a site vulnerability index to the assess colonization risk of E. murphyi . Future scenarios of ecophysiological suitability were built around the warming trends in the region. Results Both SDMs converge to predict high environmental suitability in the species' native and introduced ranges. However, the mechanistic model indicates a slightly larger invasive potential based on larval performance at different temperatures. Human activity levels across the Antarctic Peninsula play a key role in discerning site vulnerabilities. Niche suitability in Antarctica grows considerably under long‐term climate scenarios, leading to a substantially higher invasive threat to the Antarctic ecosystems. In turn changing conditions result in growing physiological mismatches with the environment in the native range in South Georgia. Main conclusions Long‐term studies of invasion potential under climate benefit from integrating ...
author2 Natural Environment Research Council
University of Birmingham
British Antarctic Survey
format Article in Journal/Newspaper
author Pertierra, Luis R.
Bartlett, Jesamine C.
Duffy, Grant A.
Vega, Greta C.
Hughes, Kevin A.
Hayward, Scott A. L.
Convey, Peter
Olalla‐Tarraga, Miguel A.
Aragón, P.
spellingShingle Pertierra, Luis R.
Bartlett, Jesamine C.
Duffy, Grant A.
Vega, Greta C.
Hughes, Kevin A.
Hayward, Scott A. L.
Convey, Peter
Olalla‐Tarraga, Miguel A.
Aragón, P.
Combining correlative and mechanistic niche models with human activity data to elucidate the invasive potential of a sub‐Antarctic insect
author_facet Pertierra, Luis R.
Bartlett, Jesamine C.
Duffy, Grant A.
Vega, Greta C.
Hughes, Kevin A.
Hayward, Scott A. L.
Convey, Peter
Olalla‐Tarraga, Miguel A.
Aragón, P.
author_sort Pertierra, Luis R.
title Combining correlative and mechanistic niche models with human activity data to elucidate the invasive potential of a sub‐Antarctic insect
title_short Combining correlative and mechanistic niche models with human activity data to elucidate the invasive potential of a sub‐Antarctic insect
title_full Combining correlative and mechanistic niche models with human activity data to elucidate the invasive potential of a sub‐Antarctic insect
title_fullStr Combining correlative and mechanistic niche models with human activity data to elucidate the invasive potential of a sub‐Antarctic insect
title_full_unstemmed Combining correlative and mechanistic niche models with human activity data to elucidate the invasive potential of a sub‐Antarctic insect
title_sort combining correlative and mechanistic niche models with human activity data to elucidate the invasive potential of a sub‐antarctic insect
publisher Wiley
publishDate 2019
url http://dx.doi.org/10.1111/jbi.13780
https://api.wiley.com/onlinelibrary/tdm/v1/articles/10.1111%2Fjbi.13780
https://onlinelibrary.wiley.com/doi/pdf/10.1111/jbi.13780
https://onlinelibrary.wiley.com/doi/full-xml/10.1111/jbi.13780
genre Antarc*
Antarctic
Antarctic Peninsula
Antarctica
Southern Ocean
genre_facet Antarc*
Antarctic
Antarctic Peninsula
Antarctica
Southern Ocean
op_source Journal of Biogeography
volume 47, issue 3, page 658-673
ISSN 0305-0270 1365-2699
op_rights http://onlinelibrary.wiley.com/termsAndConditions#vor
op_doi https://doi.org/10.1111/jbi.13780
container_title Journal of Biogeography
container_volume 47
container_issue 3
container_start_page 658
op_container_end_page 673
_version_ 1810290260508147712