Spatio-temporal analysis of alpine ecotones: A spatial explicit model targeting altitudinal vegetation shifts

Ramón Alberto Díaz-Varela, Roberto Colombo, Michele Meroni, María Silvia Calvo-Iglesias, Armando Buffoni and Antonio Tagliaferri

Ecological Modelling, 2010, vol. 221, issue 4, 621-633

Abstract: There is general agreement in literature that Alpine vegetation belt ecotones have shown a trend of upward migration in the last few decades. Despite the potential of such shifts as indicators of global change effects in mountain ecosystems, there are relatively few works focused on their assessment in a systematic and spatially explicit way. In this work our aim is to quantify the altitudinal shifts and analyse the spatial pattern dynamics of mountain ecotones. We developed a novel procedure to delineate the current and former state of three characteristic mountain ecotones, which we formalised as forest, tree and tundra lines. Our approach is based on the recognition of altitudinal extreme outposts identified with ecotone locations at a slope scale. The integration of multi-temporal datasets allows the identification and quantification of altitudinal advances and retreats in the outpost locations for a given period. We tested the method in a section of the Italian Alps for the period 1957–2003. Results show a general trend of an increase in altitude for the three ecotones, despite the occurrence of occasional decreases. We estimate decadal altitude increments of 25m for forest line, 13m for treeline and 11m for tundra line. We also identified changes in ecotone spatial morphology between the two dates, with significant implications in connectivity and colonisation dynamics.

Keywords: Mountain ecotones; Alps; Global change; Landscape metrics; Spatially explicit model; Digital elevation model (search for similar items in EconPapers)
Date: 2010
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Citations: View citations in EconPapers (2)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:ecomod:v:221:y:2010:i:4:p:621-633

DOI: 10.1016/j.ecolmodel.2009.11.010

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