Plants as bioindicator for temperature interpolation purposes : analyzing spatial correlation between botany based index of thermophily and integrated temperature characteristics

International audience The success of interpolation techniques relies heavily on the density and regularity of field reference data points. For instance temperature interpolations in the Arctic are hampered by few and scattered meteorological stations. The major objective of this study is to analyze...

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Bibliographic Details
Published in:Ecological Indicators
Main Authors: Joly, Daniel, Nilsen, Lennart, Brossard, Thierry, Elvebakk, Arve
Other Authors: Théoriser et modéliser pour aménager (UMR 6049) (ThéMA), 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), University of Tromsø (UiT)
Format: Article in Journal/Newspaper
Language:English
Published: HAL CCSD 2010
Subjects:
geo
Online Access:https://doi.org/10.1016/j.ecolind.2010.02.007
https://hal.archives-ouvertes.fr/hal-00731635
Description
Summary:International audience The success of interpolation techniques relies heavily on the density and regularity of field reference data points. For instance temperature interpolations in the Arctic are hampered by few and scattered meteorological stations. The major objective of this study is to analyze the spatial relationship between plants, defined in terms of an index of thermophily (It) and temperature distribution. The study area is located in Kongsfjorden, northwest Spitsbergen (Svalbard). A systematic recording of floristic data covering the study area was made within quadrates of 1 km × 1 km (93 units). For each of them, the It was calculated. It provides a synthetic measure by which plants are taken as temperature indicators at a long time scale. Temperature values were recorded by means of 39 temperature loggers during the summer 2000. The model for spatial interpolation of temperature was developed using multiple regression of remote sensed data (Landsat TM) and topographical features derived from a digital elevation model (DEM). Continuous temperature layers were calculated at a spatial resolution of 50 m × 50 m, and aggregated to a resolution of 1 km × 1 km in order to correspond with the observed botanical units. Different maps were produced showing spatial distribution of the modelled temperature and It. Correlations between the It and temperature values derived from the modelled temperature layers were systematically explored. Correlation between the It and temperatures works well as standard deviation of residues is 0.7 °C only. Highest correlations (r) of It and the spatial distribution of temperature were obtained for: (a) maximum average temperature for August, excluding all areas higher than 100 m above sea level (0.75), (b) average daily maximum temperature for July-October (0.67), (c) average temperature for July and August (0.64, 0.65), and (d) when temperature range is >8 °C (0.55). Areas with low correlations between It and temperature were mainly attributed to the fact that these ...