Abstract
Shrub encroachment into grassland and rocky habitats is a noticeable land cover change currently underway in temperate mountains and is a matter of concern for the sustainable management of mountain biodiversity. Current land cover products tend to underestimate the extent of mountain shrublands dominated by Ericaceae (Vaccinium spp. (species) and Rhododendron ferrugineum). In addition, mountain shrubs are often confounded with grasslands. Here, we examined the potential of anthocyanin-responsive vegetation indices to provide more accurate maps of mountain shrublands in a mountain range located in the French Alps. We relied on the multi-spectral instrument onboard the Sentinel-2A and 2B satellites and the availability of red-edge bands to calculate a Normalized Anthocyanin Reflectance Index (NARI). We used this index to quantify the autumn accumulation of anthocyanin in canopies dominated by Vaccinium spp. and Rhododendron ferrugineum and compared the effectiveness of NARI to Normalized Difference Vegetation Index (NDVI) as a basis for shrubland mapping. Photointerpretation of high-resolution aerial imagery, intensive field campaigns, and floristic surveys provided complementary data to calibrate and evaluate model performance. The proposed NARI-based model performed better than the NDVI-based model with an area under the curve (AUC) of 0.92 against 0.58. Validation of shrub cover maps based on NARI resulted in a Kappa coefficient of 0.67, which outperformed existing land cover products and resulted in a ten-fold increase in estimated area occupied by Ericaceae-dominated shrublands. We conclude that the Sentinel-2 red-edge band provides novel opportunities to detect seasonal anthocyanin accumulation in plant canopies and discuss the potential of our method to quantify long-term dynamics of shrublands in alpine and arctic contexts.
Highlights
In the context of recently observed shifts in climate [1] and vegetation [2,3] in the European Alps, efficient mapping of mountain land cover (LC) over time and space using satellite imagery has emerged as a high priority for environmental monitoring and management [4,5,6,7]
Three existing LC products were compared to our classification: (i) two classes of the 100 meter resolution 2018 CORINE Land Cover (CLC) available for Europe [8], transitional woodland-shrub (324) and moors and heathland (322), which we considered to be the equivalent of shrublands in our classification, (ii) the mixed tree-shrub-herbaceous class (100) of the 2015 Global European Space Agency Climate Change Initiative (CCI) Land Cover map at a spatial resolution of 300 m [56], and (iii) the woody moorland (36) class of the 10 meter resolution 2017 Occupation des Sols (OSO) LC map, which is only available for France [9]
Comparison between end-member pixels corresponding to leaves with and without anthocyanins demonstrated coherent results with respect to Gittelson et al [27]
Summary
In the context of recently observed shifts in climate [1] and vegetation [2,3] in the European Alps, efficient mapping of mountain land cover (LC) over time and space using satellite imagery has emerged as a high priority for environmental monitoring and management [4,5,6,7]. In addition to climate change, the European Alps have experienced widespread land abandonment during recent decades, contributing to increased woody plant cover in subalpine pastures [14,15,16]. While there is growing evidence that shrub expansion is underway in the Alps, landscape scale analysis of shrub distribution and dynamics is currently impeded by our inability to systematically distinguish shrub cover from other forms of vegetation in above treeline habitats using widely available satellite imagery. From both scientific and land management perspectives, there is a clear need to improve remote sensing-based methods for mapping shrub cover
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