Data from: Combining correlative and mechanistic niche models with human activity data to elucidate the invasive potential of a sub-Antarctic insect
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substantial spatio-temporal limitations when historical occurrence records of data-poor species provide incomplete and outdated information for niche modelling.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 va...
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ftzenodo:oai:zenodo.org:4290982 2024-09-15T17:48:23+00:00 Data from: Combining correlative and mechanistic niche models with human activity data to elucidate the invasive potential of a sub-Antarctic insect Pertierra, Luis Aragón, Pedro Olalla-Tarraga, Miguel Vega, Greta Duffy, Grant Convey, Pete Hayward, Scott Hughes, Kevin Bartlett, Jesamine 2020-12-20 https://doi.org/10.5061/dryad.x69p8czdn unknown Zenodo https://zenodo.org/communities/dryad https://doi.org/10.5061/dryad.x69p8czdn oai:zenodo.org:4290982 info:eu-repo/semantics/openAccess Creative Commons Zero v1.0 Universal https://creativecommons.org/publicdomain/zero/1.0/legalcode Chironomidae Human Footprint conservation paradox Southern Ocean info:eu-repo/semantics/other 2020 ftzenodo https://doi.org/10.5061/dryad.x69p8czdn 2024-07-26T03:24:03Z 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substantial spatio-temporal limitations when historical occurrence records of data-poor species provide incomplete and outdated information for niche modelling.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 colonization 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 on growing physiological mismatches with the environment in the native range on South Georgia. Main conclusions Long-term studies of invasion potential under climate benefit from integrating correlative predictions ... Other/Unknown Material Antarc* Antarctic Antarctic Peninsula Antarctica Southern Ocean Zenodo |
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Chironomidae Human Footprint conservation paradox Southern Ocean |
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Chironomidae Human Footprint conservation paradox Southern Ocean Pertierra, Luis Aragón, Pedro Olalla-Tarraga, Miguel Vega, Greta Duffy, Grant Convey, Pete Hayward, Scott Hughes, Kevin Bartlett, Jesamine Data from: Combining correlative and mechanistic niche models with human activity data to elucidate the invasive potential of a sub-Antarctic insect |
topic_facet |
Chironomidae Human Footprint conservation paradox Southern Ocean |
description |
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 colonization 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 on growing physiological mismatches with the environment in the native range on South Georgia. Main conclusions Long-term studies of invasion potential under climate benefit from integrating correlative predictions ... |
format |
Other/Unknown Material |
author |
Pertierra, Luis Aragón, Pedro Olalla-Tarraga, Miguel Vega, Greta Duffy, Grant Convey, Pete Hayward, Scott Hughes, Kevin Bartlett, Jesamine |
author_facet |
Pertierra, Luis Aragón, Pedro Olalla-Tarraga, Miguel Vega, Greta Duffy, Grant Convey, Pete Hayward, Scott Hughes, Kevin Bartlett, Jesamine |
author_sort |
Pertierra, Luis |
title |
Data from: Combining correlative and mechanistic niche models with human activity data to elucidate the invasive potential of a sub-Antarctic insect |
title_short |
Data from: Combining correlative and mechanistic niche models with human activity data to elucidate the invasive potential of a sub-Antarctic insect |
title_full |
Data from: Combining correlative and mechanistic niche models with human activity data to elucidate the invasive potential of a sub-Antarctic insect |
title_fullStr |
Data from: Combining correlative and mechanistic niche models with human activity data to elucidate the invasive potential of a sub-Antarctic insect |
title_full_unstemmed |
Data from: Combining correlative and mechanistic niche models with human activity data to elucidate the invasive potential of a sub-Antarctic insect |
title_sort |
data from: combining correlative and mechanistic niche models with human activity data to elucidate the invasive potential of a sub-antarctic insect |
publisher |
Zenodo |
publishDate |
2020 |
url |
https://doi.org/10.5061/dryad.x69p8czdn |
genre |
Antarc* Antarctic Antarctic Peninsula Antarctica Southern Ocean |
genre_facet |
Antarc* Antarctic Antarctic Peninsula Antarctica Southern Ocean |
op_relation |
https://zenodo.org/communities/dryad https://doi.org/10.5061/dryad.x69p8czdn oai:zenodo.org:4290982 |
op_rights |
info:eu-repo/semantics/openAccess Creative Commons Zero v1.0 Universal https://creativecommons.org/publicdomain/zero/1.0/legalcode |
op_doi |
https://doi.org/10.5061/dryad.x69p8czdn |
_version_ |
1810289549877706752 |