Analysis of plant colonization on an arctic moraine since the end of the Little Ice Age using remotely sensed data and a Bayesian approach.

• Published in: Remote Sensing of Environment
• Main Authors: Moreau, Myrtille, Laffly, Dominique, Joly, Daniel, Brossard, Thierry
• Other Authors: Laboratoire de Géographie Physique et Environnementale (GEOLAB), Université Blaise Pascal - Clermont-Ferrand 2 (UBP)-Université Clermont Auvergne 2017-2020 (UCA 2017-2020 )-Université Clermont Auvergne (UCA)-Institut Sciences de l'Homme et de la Société (IR SHS UNILIM), Université de Limoges (UNILIM)-Université de Limoges (UNILIM)-Centre National de la Recherche Scientifique (CNRS), Géographie de l'environnement (GEODE), Université Toulouse - Jean Jaurès (UT2J)-Centre National de la Recherche Scientifique (CNRS), 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)
• Format: Article in Journal/Newspaper
• Language: English
• Published: HAL CCSD 2005
• Subjects: Little Ice Age; Bayesian approach; Midre Love´nbreen fore field; Plant colonization; [SHS.GEO]Humanities and Social Sciences/Geography; Arctic; Svalbard; Climate change; glacier
• Online Access: https://halshs.archives-ouvertes.fr/halshs-00468659; https://doi.org/10.1016/j.rse.2005.03.017

International audience Young moraines less than 100 years old are considered as key areas for monitoring the effects of climate change since the end of the Little Ice Age. One way of documenting this change is by recognizing and characterizing the different plant colonization stages and trends that occur on these relatively new environments. Previous studies have shown that remotely sensed data alone are not sufficient to map the vegetation over these types of landscapes because the most significant part of the radiometric information is related to mineral landscape components. Therefore, the authors used an indirect approach which consisted in the following steps. 1 – An optimized sampling procedure was used to collect georeferenced vegetation plot data. A multivariate analysis was then used to define vegetation types that could be related to different colonization stages and environmental contexts. 2 – Color infrared aerial photographs where then used to produce a baseline vegetation map. This map was thenintegrated into a data base along with other environment factors known to control plant colonization processes, such as climate (wind, temperature), physical landscape components (habitat characteristics) and morphodynamic processes (runoff). 3 – A Bayesian model using conditional probabilities was used to identify the primary environmental habitats corresponding to the different vegetation types. This protocol was tested on the fore field of the Midre Lovénbreen (Svalbard) glacier where several vegetation belts correspond to well defined stage of deglaciation and corresponding local conditions such as microtopography, microclimate and runoff dynamics.