Modeling spatial covariation of summer temperatures and bio-indicators in an Arctic coastal area
International audience In the Arctic, temperature is a major environmental factor controlling the occurrence, abundance and distribution of plants at regional and local scales alike. This means that statistical models of temperature distribution can predict the distribution of plant species or commu...
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ftunivbourgogne:oai:HAL:hal-00911237v1 2024-09-15T18:38:27+00:00 Modeling spatial covariation of summer temperatures and bio-indicators in an Arctic coastal area Nilsen, Lennart Joly, Daniel Elvebakk, Arve Brossard, Thierry University of Tromsø (UiT) Théoriser et modéliser pour aménager (UMR 6049) (ThéMA) Université de Bourgogne (UB)-Centre National de la Recherche Scientifique (CNRS)-Université de Franche-Comté (UFC) Université Bourgogne Franche-Comté COMUE (UBFC)-Université Bourgogne Franche-Comté COMUE (UBFC) 2013-11-19 https://hal.science/hal-00911237 https://doi.org/10.3354/cr01173 en eng HAL CCSD Inter Research info:eu-repo/semantics/altIdentifier/doi/10.3354/cr01173 hal-00911237 https://hal.science/hal-00911237 doi:10.3354/cr01173 ISSN: 0936-577X EISSN: 1616-1572 Climate Research https://hal.science/hal-00911237 Climate Research, 2013, 58 (1), pp.1-13. ⟨10.3354/cr01173⟩ Temperature vegetation bio-indicators rRegression analysis Svalbard [SHS.GEO]Humanities and Social Sciences/Geography info:eu-repo/semantics/article Journal articles 2013 ftunivbourgogne https://doi.org/10.3354/cr01173 2024-07-08T23:45:11Z International audience In the Arctic, temperature is a major environmental factor controlling the occurrence, abundance and distribution of plants at regional and local scales alike. This means that statistical models of temperature distribution can predict the distribution of plant species or communities. Conversely, certain plant taxa make good bio-indicators reflecting long-term thermal conditions in a given habitat. Both these assumptions were taken into account when modelling the spatial relationship between plants and temperature. This work continues a previous preliminary 1 yr study based on correlations between a plant-based index of thermophily (It) and different synthetic temperature distribution characteristics. To strengthen confidence in the results and conclusions, more temperature data were collected through a field campaign conducted over a further 5 yr period (2001 to 2005). The goals here were (1) to establish an accurate interpolation model capable of restoring, at local scale, the continuous summertime thermal raster surface, (2) to evaluate the capacity of the temperature values obtained from the model to predict the distribution of It, and (3) to extrapolate temperature surfaces from this It. The results show that the mutual predictive power between temperature and It is satisfactory and that the model can be applied to neighbouring areas, although the present study area is too small to define the geographical limits of extrapolation. This predictive power declines where local landscape structures are heterogeneous. Correlations between It and growing degree day (GDD) values derived from the modelled temperature layers were systematically analysed in order to identify conditions in which this covariation works or fails. Article in Journal/Newspaper Svalbard Université de Bourgogne (UB): HAL Climate Research 58 1 1 13 |
institution |
Open Polar |
collection |
Université de Bourgogne (UB): HAL |
op_collection_id |
ftunivbourgogne |
language |
English |
topic |
Temperature vegetation bio-indicators rRegression analysis Svalbard [SHS.GEO]Humanities and Social Sciences/Geography |
spellingShingle |
Temperature vegetation bio-indicators rRegression analysis Svalbard [SHS.GEO]Humanities and Social Sciences/Geography Nilsen, Lennart Joly, Daniel Elvebakk, Arve Brossard, Thierry Modeling spatial covariation of summer temperatures and bio-indicators in an Arctic coastal area |
topic_facet |
Temperature vegetation bio-indicators rRegression analysis Svalbard [SHS.GEO]Humanities and Social Sciences/Geography |
description |
International audience In the Arctic, temperature is a major environmental factor controlling the occurrence, abundance and distribution of plants at regional and local scales alike. This means that statistical models of temperature distribution can predict the distribution of plant species or communities. Conversely, certain plant taxa make good bio-indicators reflecting long-term thermal conditions in a given habitat. Both these assumptions were taken into account when modelling the spatial relationship between plants and temperature. This work continues a previous preliminary 1 yr study based on correlations between a plant-based index of thermophily (It) and different synthetic temperature distribution characteristics. To strengthen confidence in the results and conclusions, more temperature data were collected through a field campaign conducted over a further 5 yr period (2001 to 2005). The goals here were (1) to establish an accurate interpolation model capable of restoring, at local scale, the continuous summertime thermal raster surface, (2) to evaluate the capacity of the temperature values obtained from the model to predict the distribution of It, and (3) to extrapolate temperature surfaces from this It. The results show that the mutual predictive power between temperature and It is satisfactory and that the model can be applied to neighbouring areas, although the present study area is too small to define the geographical limits of extrapolation. This predictive power declines where local landscape structures are heterogeneous. Correlations between It and growing degree day (GDD) values derived from the modelled temperature layers were systematically analysed in order to identify conditions in which this covariation works or fails. |
author2 |
University of Tromsø (UiT) Théoriser et modéliser pour aménager (UMR 6049) (ThéMA) Université de Bourgogne (UB)-Centre National de la Recherche Scientifique (CNRS)-Université de Franche-Comté (UFC) Université Bourgogne Franche-Comté COMUE (UBFC)-Université Bourgogne Franche-Comté COMUE (UBFC) |
format |
Article in Journal/Newspaper |
author |
Nilsen, Lennart Joly, Daniel Elvebakk, Arve Brossard, Thierry |
author_facet |
Nilsen, Lennart Joly, Daniel Elvebakk, Arve Brossard, Thierry |
author_sort |
Nilsen, Lennart |
title |
Modeling spatial covariation of summer temperatures and bio-indicators in an Arctic coastal area |
title_short |
Modeling spatial covariation of summer temperatures and bio-indicators in an Arctic coastal area |
title_full |
Modeling spatial covariation of summer temperatures and bio-indicators in an Arctic coastal area |
title_fullStr |
Modeling spatial covariation of summer temperatures and bio-indicators in an Arctic coastal area |
title_full_unstemmed |
Modeling spatial covariation of summer temperatures and bio-indicators in an Arctic coastal area |
title_sort |
modeling spatial covariation of summer temperatures and bio-indicators in an arctic coastal area |
publisher |
HAL CCSD |
publishDate |
2013 |
url |
https://hal.science/hal-00911237 https://doi.org/10.3354/cr01173 |
genre |
Svalbard |
genre_facet |
Svalbard |
op_source |
ISSN: 0936-577X EISSN: 1616-1572 Climate Research https://hal.science/hal-00911237 Climate Research, 2013, 58 (1), pp.1-13. ⟨10.3354/cr01173⟩ |
op_relation |
info:eu-repo/semantics/altIdentifier/doi/10.3354/cr01173 hal-00911237 https://hal.science/hal-00911237 doi:10.3354/cr01173 |
op_doi |
https://doi.org/10.3354/cr01173 |
container_title |
Climate Research |
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58 |
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1 |
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1 |
op_container_end_page |
13 |
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1810482861287931904 |