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

Résumé En

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.