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A new method for quantifying treeline-ecotone change based on multiple spatial pattern dimensions
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DOI：10.1007/s10980-022-01589-4.png)
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Context Treeline-ecotone spatial patterns and their dynamics reflect underlying processes. Changes in ecotone pattern may reflect changes in natural drivers or land-use practices. However, characterizing these dynamics presents a major challenge, limiting our ability to map, understand and predict changes in the upper limits of mountain forests. Objective This paper proposes a new method using multiple pattern dimensions to describe treeline-ecotone spatial pattern shifts. This standardized protocol should be able to (i) distinguish different types of treeline-ecotone patterns within a large study area, (ii) characterize temporal pattern shifts in spatial pattern between two or more dates. Method We mapped alpine treeline ecotones (ATE) at 648 sites in the eastern French Pyrenees using aerial images from similar to 1955 and similar to 2015, identifying forest and non-forest areas at the hillslope scale. Extracted patch metrics were summarized using a Principle Component Analysis (PCA) and spatial pattern change was quantified from the shift in the PCA space and compared to elevational shifts. Results Three clusters of patterns were distinguished: diffuse, discrete and island-forming ATEs. Between 1955 and 2015, about half of the sites changed from one pattern cluster to another. Shifts into discrete ATEs were associated with smaller and negative elevational shifts, while shifts into diffuse ATEs coincided with the highest positive elevational shifts. Conclusion The proposed method allows a standardized and repeatable quantification of vegetation pattern change in alpine treeline ecotones based on historical aerial imagery. Seeing the importance of treeline-ecotone shifts for alpine biodiversity, we encourage the use of this protocol to better understand treeline dynamics at treelines globally.
Keyword:
Alpine treeline ecotone
Landscape metrics
Structural shift
Spatio-temporal PCA
French Pyrenees
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3.7
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3.8K
被引数:
1.4W
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