Modeling spatial covariation of summer temperatures and bio-indicators in an Arctic coastal area
| Autor: | Thierry Brossard, Daniel Joly, Arve Elvebakk, Lennart Nilsen |
|---|---|
| Přispěvatelé: | University of Tromsø ( UiT ), Théoriser et modéliser pour aménager ( ThéMA ), Université de Bourgogne ( UB ) -Centre National de la Recherche Scientifique ( CNRS ) -Université de Franche-Comté ( UFC ), 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), Centre National de la Recherche Scientifique (CNRS)-Université de Bourgogne (UB)-Université de Franche-Comté (UFC) |
| Jazyk: | angličtina |
| Rok vydání: | 2013 |
| Předmět: |
0106 biological sciences
Atmospheric Science 010504 meteorology & atmospheric sciences Extrapolation 010603 evolutionary biology 01 natural sciences [ SHS.GEO ] Humanities and Social Sciences/Geography Svalbard Abundance (ecology) vegetation Environmental Chemistry 0105 earth and related environmental sciences General Environmental Science Temperature Regression analysis Statistical model Growing degree-day Vegetation [SHS.GEO]Humanities and Social Sciences/Geography 15. Life on land bio-indicators rRegression analysis Geography Habitat Arctic 13. Climate action Climatology |
| Zdroj: | Climate Research Climate Research, Inter Research, 2013, 58 (1), pp.1-13. 〈10.3354/cr01173 〉 Climate Research, Inter Research, 2013, 58 (1), pp.1-13. ⟨10.3354/cr01173⟩ |
| ISSN: | 0936-577X 1616-1572 |
| DOI: | 10.3354/cr01173 |
| Popis: | 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. |
| Databáze: | OpenAIRE |
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